{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FSRS4Anki Optimizer Easy & Hard Bonus\n",
    "\n",
    "[![open in colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/open-spaced-repetition/fsrs4anki/blob/main/archive/candidate/easy-hard-bonus.ipynb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Here are some settings that you need to replace before running this optimizer.\n",
    "\n",
    "filename = \"../collection-2022-09-18@13-21-58.colpkg\"\n",
    "# If you upload deck file, replace it with your deck filename. E.g., ALL__Learning.apkg\n",
    "# If you upload collection file, replace it with your colpgk filename. E.g., collection-2022-09-18@13-21-58.colpkg\n",
    "\n",
    "# Replace it with your timezone. I'm in China, so I use Asia/Shanghai.\n",
    "# You can find your timezone here: https://gist.github.com/heyalexej/8bf688fd67d7199be4a1682b3eec7568\n",
    "timezone = 'Asia/Shanghai'\n",
    "\n",
    "# Replace it with your Anki's setting in Preferences -> Scheduling.\n",
    "next_day_starts_at = 4\n",
    "\n",
    "# Replace it if you don't want the optimizer to use the review logs before a specific date.\n",
    "revlog_start_date = \"2006-10-05\"\n",
    "\n",
    "# Set it to True if you don't want the optimizer to use the review logs from suspended cards.\n",
    "filter_out_suspended_cards = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import zipfile\n",
    "import sqlite3\n",
    "import time\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "import math\n",
    "from typing import List, Optional\n",
    "from datetime import timedelta, datetime\n",
    "import statsmodels.api as sm\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as ticker\n",
    "import torch\n",
    "from torch import nn\n",
    "from torch import Tensor\n",
    "from torch.utils.data import Dataset, DataLoader, Sampler\n",
    "from torch.nn.utils.rnn import pad_sequence, pack_padded_sequence, pad_packed_sequence\n",
    "from sklearn.model_selection import StratifiedGroupKFold\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "from itertools import accumulate\n",
    "from tqdm.auto import tqdm\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
    "tqdm.pandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Deck file extracted successfully!\n",
      "revlog.csv saved.\n",
      "Trainset saved.\n",
      "Retention calculated.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "cb40308bfffb4daaa36196acb19b3300",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/26286 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stability calculated.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3356f0d87bc74803a7f5b931cc4d516c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "analysis:   0%|          | 0/489 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Analysis saved!\n",
      "1:again, 2:hard, 3:good, 4:easy\n",
      "      r_history  avg_interval  avg_retention  stability  factor  group_cnt\n",
      "              1           1.1          0.892        1.0     inf       2063\n",
      "            1,3           3.1          0.920        4.0    4.00       1600\n",
      "          1,3,3           7.1          0.910        7.9    1.98       1320\n",
      "        1,3,3,3          16.6          0.862       10.8    1.37        986\n",
      "      1,3,3,3,3          36.5          0.840       22.3    2.06        659\n",
      "    1,3,3,3,3,3          77.0          0.861       36.4    1.63        358\n",
      "  1,3,3,3,3,3,3         117.9          0.906       38.5    1.06        177\n",
      "              2           1.0          0.902        1.1     inf        240\n",
      "            2,3           3.5          0.946        8.2    7.45        201\n",
      "          2,3,3          11.4          0.890        7.6    0.93        162\n",
      "              3           1.1          0.977        5.0     inf       4669\n",
      "            3,3           3.3          0.967       12.0    2.40       4211\n",
      "          3,3,3           8.1          0.960       19.9    1.66       3757\n",
      "        3,3,3,3          18.3          0.941       41.5    2.09       2834\n",
      "      3,3,3,3,3          35.2          0.930       50.5    1.22       1761\n",
      "    3,3,3,3,3,3          64.9          0.929       97.9    1.94       1102\n",
      "  3,3,3,3,3,3,3         100.9          0.949      143.0    1.46        530\n",
      "3,3,3,3,3,3,3,3         133.6          0.990     1821.9   12.74        131\n",
      "              4           2.0          0.976       10.7     inf       2789\n",
      "            4,3           3.7          0.976       20.4    1.91       2293\n",
      "          4,3,3           8.3          0.967       32.5    1.59       2051\n",
      "        4,3,3,3          19.8          0.958       54.5    1.68       1700\n",
      "      4,3,3,3,3          41.0          0.958       99.5    1.83       1148\n",
      "    4,3,3,3,3,3          68.1          0.956      116.1    1.17        521\n",
      "  4,3,3,3,3,3,3          78.5          0.979      110.7    0.95        248\n",
      "4,3,3,3,3,3,3,3         114.1          0.984      177.8    1.61        166\n"
     ]
    }
   ],
   "source": [
    "\"\"\"Step 1\"\"\"\n",
    "# Extract the collection file or deck file to get the .anki21 database.\n",
    "with zipfile.ZipFile(f'{filename}', 'r') as zip_ref:\n",
    "    zip_ref.extractall('./')\n",
    "    print(\"Deck file extracted successfully!\")\n",
    "\n",
    "\"\"\"Step 2\"\"\"\n",
    "if os.path.isfile(\"collection.anki21b\"):\n",
    "    os.remove(\"collection.anki21b\")\n",
    "    raise Exception(\n",
    "        \"Please export the file with `support older Anki versions` if you use the latest version of Anki.\")\n",
    "elif os.path.isfile(\"collection.anki21\"):\n",
    "    con = sqlite3.connect(\"collection.anki21\")\n",
    "elif os.path.isfile(\"collection.anki2\"):\n",
    "    con = sqlite3.connect(\"collection.anki2\")\n",
    "else:\n",
    "    raise Exception(\"Collection not exist!\")\n",
    "cur = con.cursor()\n",
    "res = cur.execute(f\"\"\"\n",
    "SELECT *\n",
    "FROM revlog\n",
    "WHERE cid IN (\n",
    "    SELECT id\n",
    "    FROM cards\n",
    "    {\"WHERE queue != -1\" if filter_out_suspended_cards else \"\"}\n",
    ")\n",
    "\"\"\"\n",
    ")\n",
    "revlog = res.fetchall()\n",
    "if len(revlog) == 0:\n",
    "    raise Exception(\"No review log found!\")\n",
    "df = pd.DataFrame(revlog)\n",
    "df.columns = ['id', 'cid', 'usn', 'r', 'ivl', 'last_lvl', 'factor', 'time', 'type']\n",
    "df = df[(df['cid'] <= time.time() * 1000) &\n",
    "        (df['id'] <= time.time() * 1000)].copy()\n",
    "\n",
    "df_set_due_date = df[(df['type'] == 4) & (df['ivl'] > 0)]\n",
    "df.drop(df_set_due_date.index, inplace=True)\n",
    "\n",
    "df['create_date'] = pd.to_datetime(df['cid'] // 1000, unit='s')\n",
    "df['create_date'] = df['create_date'].dt.tz_localize('UTC').dt.tz_convert(timezone)\n",
    "df['review_date'] = pd.to_datetime(df['id'] // 1000, unit='s')\n",
    "df['review_date'] = df['review_date'].dt.tz_localize('UTC').dt.tz_convert(timezone)\n",
    "df.drop(df[df['review_date'].dt.year < 2006].index, inplace=True)\n",
    "df.sort_values(by=['cid', 'id'], inplace=True, ignore_index=True)\n",
    "\n",
    "df['is_learn_start'] = (df['type'] == 0) & (df['type'].shift() != 0)\n",
    "df['sequence_group'] = df['is_learn_start'].cumsum()\n",
    "last_learn_start = df[df['is_learn_start']].groupby('cid')['sequence_group'].last()\n",
    "df['last_learn_start'] = df['cid'].map(last_learn_start).fillna(0).astype(int)\n",
    "df['mask'] = df['last_learn_start'] <= df['sequence_group']\n",
    "df = df[df['mask'] == True].copy()\n",
    "df.drop(columns=['is_learn_start', 'sequence_group', 'last_learn_start', 'mask'], inplace=True)\n",
    "df = df[(df['type'] != 4)].copy()\n",
    "\n",
    "type_sequence = np.array(df['type'])\n",
    "time_sequence = np.array(df['time'])\n",
    "df.to_csv(\"revlog.csv\", index=False)\n",
    "print(\"revlog.csv saved.\")\n",
    "\n",
    "df = df[(df['type'] != 3) | (df['factor'] != 0)].copy()\n",
    "df['real_days'] = df['review_date'] - timedelta(hours=int(next_day_starts_at))\n",
    "df['real_days'] = pd.DatetimeIndex(df['real_days'].dt.floor('D', ambiguous='infer', nonexistent='shift_forward')).to_julian_date()\n",
    "df.drop_duplicates(['cid', 'real_days'], keep='first', inplace=True)\n",
    "df['delta_t'] = df.real_days.diff()\n",
    "df.dropna(inplace=True)\n",
    "df['i'] = df.groupby('cid').cumcount() + 1\n",
    "df.loc[df['i'] == 1, 'delta_t'] = 0\n",
    "df = df.groupby('cid').filter(lambda group: group['type'].iloc[0] == 0)\n",
    "df['prev_type'] = df.groupby('cid')['type'].shift(1).fillna(0).astype(int)\n",
    "df['helper'] = ((df['type'] == 0) & ((df['prev_type'] == 1) | (df['prev_type'] == 2)) & (df['i'] > 1)).astype(int)\n",
    "df['helper'] = df.groupby('cid')['helper'].cumsum()\n",
    "df = df[df['helper'] == 0]\n",
    "del df['prev_type']\n",
    "del df['helper']\n",
    "\n",
    "def cum_concat(x):\n",
    "    return list(accumulate(x))\n",
    "\n",
    "t_history = df.groupby('cid', group_keys=False)['delta_t'].apply(lambda x: cum_concat([[int(i)] for i in x]))\n",
    "df['t_history']=[','.join(map(str, item[:-1])) for sublist in t_history for item in sublist]\n",
    "r_history = df.groupby('cid', group_keys=False)['r'].apply(lambda x: cum_concat([[i] for i in x]))\n",
    "df['r_history']=[','.join(map(str, item[:-1])) for sublist in r_history for item in sublist]\n",
    "df = df.groupby('cid').filter(lambda group: group['id'].min() > time.mktime(datetime.strptime(revlog_start_date, \"%Y-%m-%d\").timetuple()) * 1000)\n",
    "df['y'] = df['r'].map(lambda x: {1: 0, 2: 1, 3: 1, 4: 1}[x])\n",
    "df.to_csv('revlog_history.tsv', sep=\"\\t\", index=False)\n",
    "print(\"Trainset saved.\")\n",
    "\n",
    "df['retention'] = df.groupby(by=['r_history', 'delta_t'], group_keys=False)['y'].transform('mean')\n",
    "df['total_cnt'] = df.groupby(by=['r_history', 'delta_t'], group_keys=False)['id'].transform('count')\n",
    "print(\"Retention calculated.\")\n",
    "\n",
    "df = df.drop(columns=['id', 'cid', 'usn', 'ivl', 'last_lvl', 'factor', 'time', 'type', 'create_date', 'review_date', 'real_days', 'r', 't_history', 'y'])\n",
    "df.drop_duplicates(inplace=True)\n",
    "df['retention'] = df['retention'].map(lambda x: max(min(0.99, x), 0.01))\n",
    "\n",
    "def cal_stability(group: pd.DataFrame) -> pd.DataFrame:\n",
    "    group_cnt = sum(group['total_cnt'])\n",
    "    if group_cnt < 10:\n",
    "        return pd.DataFrame()\n",
    "    group['group_cnt'] = group_cnt\n",
    "    if group['i'].values[0] > 1:\n",
    "        r_ivl_cnt = sum(group['delta_t'] * group['retention'].map(np.log) * pow(group['total_cnt'], 2))\n",
    "        ivl_ivl_cnt = sum(group['delta_t'].map(lambda x: x ** 2) * pow(group['total_cnt'], 2))\n",
    "        group['stability'] = round(np.log(0.9) / (r_ivl_cnt / ivl_ivl_cnt), 1)\n",
    "    else:\n",
    "        group['stability'] = 0.0\n",
    "    group['avg_retention'] = round(sum(group['retention'] * pow(group['total_cnt'], 2)) / sum(pow(group['total_cnt'], 2)), 3)\n",
    "    group['avg_interval'] = round(sum(group['delta_t'] * pow(group['total_cnt'], 2)) / sum(pow(group['total_cnt'], 2)), 1)\n",
    "    del group['total_cnt']\n",
    "    del group['retention']\n",
    "    del group['delta_t']\n",
    "    return group\n",
    "\n",
    "df = df.groupby(by=['r_history'], group_keys=False).progress_apply(cal_stability)\n",
    "print(\"Stability calculated.\")\n",
    "df.reset_index(drop = True, inplace = True)\n",
    "df.drop_duplicates(inplace=True)\n",
    "df.sort_values(by=['r_history'], inplace=True, ignore_index=True)\n",
    "\n",
    "if df.shape[0] > 0:\n",
    "    for idx in tqdm(df.index, desc=\"analysis\"):\n",
    "        item = df.loc[idx]\n",
    "        index = df[(df['i'] == item['i'] + 1) & (df['r_history'].str.startswith(item['r_history']))].index\n",
    "        df.loc[index, 'last_stability'] = item['stability']\n",
    "    df['factor'] = round(df['stability'] / df['last_stability'], 2)\n",
    "    df = df[(df['i'] >= 2) & (df['group_cnt'] >= 100)].copy()\n",
    "    df['last_recall'] = df['r_history'].map(lambda x: x[-1])\n",
    "    df = df[df.groupby(['i', 'r_history'], group_keys=False)['group_cnt'].transform(max) == df['group_cnt']]\n",
    "    df.to_csv('./stability_for_analysis.tsv', sep='\\t', index=None)\n",
    "    print(\"Analysis saved!\")\n",
    "    caption = \"1:again, 2:hard, 3:good, 4:easy\\n\"\n",
    "    analysis = df[df['r_history'].str.contains(r'^[1-4][^124]*$', regex=True)][['r_history', 'avg_interval', 'avg_retention', 'stability', 'factor', 'group_cnt']].to_string(index=False)\n",
    "    print(caption + analysis)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "init_w = [1, 1, 5, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2, -0.2, 0.2, 1, 0.8, 1.2]\n",
    "\n",
    "class FSRS(nn.Module):\n",
    "    def __init__(self, w: List[float]):\n",
    "        super(FSRS, self).__init__()\n",
    "        self.w = nn.Parameter(torch.tensor(w, dtype=torch.float32))\n",
    "\n",
    "    def stability_after_success(self, state: Tensor, new_d: Tensor, r: Tensor, rating: Tensor) -> Tensor:\n",
    "        hard_bonus = torch.where(rating == 2, self.w[13], 1)\n",
    "        easy_bonus = torch.where(rating == 4, self.w[14], 1)\n",
    "        new_s = state[:,0] * (1 + torch.exp(self.w[6]) *\n",
    "                        (11 - new_d) *\n",
    "                        torch.pow(state[:,0], self.w[7]) *\n",
    "                        (torch.exp((1 - r) * self.w[8]) - 1) * hard_bonus * easy_bonus)\n",
    "        return new_s\n",
    "\n",
    "    def stability_after_failure(self, state: Tensor, new_d: Tensor, r: Tensor) -> Tensor:\n",
    "        new_s = self.w[9] * torch.pow(new_d, self.w[10]) * torch.pow(\n",
    "            state[:,0], self.w[11]) * torch.exp((1 - r) * self.w[12])\n",
    "        return new_s\n",
    "\n",
    "    def step(self, X: Tensor, state: Tensor) -> Tensor:\n",
    "        '''\n",
    "        :param X: shape[batch_size, 2], X[:,0] is elapsed time, X[:,1] is rating\n",
    "        :param state: shape[batch_size, 2], state[:,0] is stability, state[:,1] is difficulty\n",
    "        :return state:\n",
    "        '''\n",
    "        if torch.equal(state, torch.zeros_like(state)):\n",
    "            # first learn, init memory states\n",
    "            new_s = self.w[0] + self.w[1] * (X[:,1] - 1)\n",
    "            new_d = self.w[2] + self.w[3] * (X[:,1] - 3)\n",
    "            new_d = new_d.clamp(1, 10)\n",
    "        else:\n",
    "            r = torch.exp(np.log(0.9) * X[:,0] / state[:,0])\n",
    "            new_d = state[:,1] + self.w[4] * (X[:,1] - 3)\n",
    "            new_d = self.mean_reversion(self.w[2], new_d)\n",
    "            new_d = new_d.clamp(1, 10)\n",
    "            condition = X[:,1] > 1\n",
    "            new_s = torch.where(condition, self.stability_after_success(state, new_d, r, X[:,1]), self.stability_after_failure(state, new_d, r))\n",
    "        new_s = new_s.clamp(0.1, 36500)\n",
    "        return torch.stack([new_s, new_d], dim=1)\n",
    "\n",
    "    def forward(self, inputs: Tensor, state: Optional[Tensor]=None) -> Tensor:\n",
    "        '''\n",
    "        :param inputs: shape[seq_len, batch_size, 2]\n",
    "        '''\n",
    "        if state is None:\n",
    "            state = torch.zeros((inputs.shape[1], 2))\n",
    "        outputs = []\n",
    "        for X in inputs:\n",
    "            state = self.step(X, state)\n",
    "            outputs.append(state)\n",
    "        return torch.stack(outputs), state\n",
    "\n",
    "    def mean_reversion(self, init: Tensor, current: Tensor) -> Tensor:\n",
    "        return self.w[5] * init + (1-self.w[5]) * current\n",
    "\n",
    "class WeightClipper:\n",
    "    def __init__(self, frequency: int=1):\n",
    "        self.frequency = frequency\n",
    "\n",
    "    def __call__(self, module):\n",
    "        if hasattr(module, 'w'):\n",
    "            w = module.w.data\n",
    "            w[0] = w[0].clamp(0.1, 10)\n",
    "            w[1] = w[1].clamp(0.1, 5)\n",
    "            w[2] = w[2].clamp(1, 10)\n",
    "            w[3] = w[3].clamp(-5, -0.1)\n",
    "            w[4] = w[4].clamp(-5, -0.1)\n",
    "            w[5] = w[5].clamp(0.05, 0.5)\n",
    "            w[6] = w[6].clamp(0, 2)\n",
    "            w[7] = w[7].clamp(-0.8, -0.15)\n",
    "            w[8] = w[8].clamp(0.01, 1.5)\n",
    "            w[9] = w[9].clamp(0.5, 5)\n",
    "            w[10] = w[10].clamp(-2, -0.01)\n",
    "            w[11] = w[11].clamp(0.01, 0.9)\n",
    "            w[12] = w[12].clamp(0.01, 2)\n",
    "            w[13] = w[13].clamp(0.01, 1)\n",
    "            w[14] = w[14].clamp(1, 2.5)\n",
    "            module.w.data = w\n",
    "\n",
    "def lineToTensor(line: str) -> Tensor:\n",
    "    ivl = line[0].split(',')\n",
    "    response = line[1].split(',')\n",
    "    tensor = torch.zeros(len(response), 2)\n",
    "    for li, response in enumerate(response):\n",
    "        tensor[li][0] = int(ivl[li])\n",
    "        tensor[li][1] = int(response)\n",
    "    return tensor\n",
    "\n",
    "class RevlogDataset(Dataset):\n",
    "    def __init__(self, dataframe: pd.DataFrame):\n",
    "        if dataframe.empty:\n",
    "            raise ValueError('Training data is inadequate.')\n",
    "        padded = pad_sequence(dataframe['tensor'].to_list(), batch_first=True, padding_value=0)\n",
    "        self.x_train = padded.int()\n",
    "        self.t_train = torch.tensor(dataframe['delta_t'].values, dtype=torch.int)\n",
    "        self.y_train = torch.tensor(dataframe['y'].values, dtype=torch.float)\n",
    "        self.seq_len = torch.tensor(dataframe['tensor'].map(len).values, dtype=torch.long)\n",
    "\n",
    "    def __getitem__(self, idx):\n",
    "        return self.x_train[idx], self.t_train[idx], self.y_train[idx], self.seq_len[idx]\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.y_train)\n",
    "\n",
    "class RevlogSampler(Sampler[List[int]]):\n",
    "    def __init__(self, data_source: RevlogDataset, batch_size: int):\n",
    "        self.data_source = data_source\n",
    "        self.batch_size = batch_size\n",
    "        lengths = np.array(data_source.seq_len)\n",
    "        indices = np.argsort(lengths)\n",
    "        full_batches, remainder = divmod(indices.size, self.batch_size)\n",
    "        if full_batches > 0:\n",
    "            if remainder == 0:\n",
    "                self.batch_indices = np.split(indices, full_batches)\n",
    "            else:\n",
    "                self.batch_indices = np.split(indices[:-remainder], full_batches)\n",
    "        else:\n",
    "            self.batch_indices = []\n",
    "        if remainder > 0:\n",
    "            self.batch_indices.append(indices[-remainder:])\n",
    "        self.batch_nums = len(self.batch_indices)\n",
    "        # seed = int(torch.empty((), dtype=torch.int64).random_().item())\n",
    "        seed = 2023\n",
    "        self.generator = torch.Generator()\n",
    "        self.generator.manual_seed(seed)\n",
    "\n",
    "    def __iter__(self):\n",
    "        yield from (self.batch_indices[idx] for idx in torch.randperm(self.batch_nums, generator=self.generator).tolist())\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.data_source)\n",
    "\n",
    "\n",
    "def collate_fn(batch):\n",
    "    sequences, delta_ts, labels, seq_lens = zip(*batch)\n",
    "    sequences_packed = pack_padded_sequence(torch.stack(sequences, dim=1), lengths=torch.stack(seq_lens), batch_first=False, enforce_sorted=False)\n",
    "    sequences_padded, length = pad_packed_sequence(sequences_packed, batch_first=False)\n",
    "    sequences_padded = torch.as_tensor(sequences_padded)\n",
    "    seq_lens = torch.as_tensor(length)\n",
    "    delta_ts = torch.as_tensor(delta_ts)\n",
    "    labels = torch.as_tensor(labels)\n",
    "    return sequences_padded, delta_ts, labels, seq_lens\n",
    "\n",
    "class Trainer:\n",
    "    def __init__(self, train_set: pd.DataFrame, test_set: pd.DataFrame, init_w: List[float], n_epoch: int=1, lr: float=1e-2, batch_size: int=256) -> None:\n",
    "        self.model = FSRS(init_w)\n",
    "        self.optimizer = torch.optim.Adam(self.model.parameters(), lr=lr)\n",
    "        self.clipper = WeightClipper()\n",
    "        self.batch_size = batch_size\n",
    "        self.build_dataset(train_set, test_set)\n",
    "        self.n_epoch = n_epoch\n",
    "        self.batch_nums = self.next_train_data_loader.batch_sampler.batch_nums\n",
    "        self.scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(self.optimizer, T_max=self.batch_nums * n_epoch)\n",
    "        self.avg_train_losses = []\n",
    "        self.avg_eval_losses = []\n",
    "        self.loss_fn = nn.BCELoss(reduction='sum')\n",
    "\n",
    "    def build_dataset(self, train_set: pd.DataFrame, test_set: pd.DataFrame):\n",
    "        pre_train_set = train_set[train_set['i'] == 2]\n",
    "        self.pre_train_set = RevlogDataset(pre_train_set)\n",
    "        sampler = RevlogSampler(self.pre_train_set, batch_size=self.batch_size)\n",
    "        self.pre_train_data_loader = DataLoader(self.pre_train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        next_train_set = train_set[train_set['i'] > 2]\n",
    "        self.next_train_set = RevlogDataset(next_train_set)\n",
    "        sampler = RevlogSampler(self.next_train_set, batch_size=self.batch_size)\n",
    "        self.next_train_data_loader = DataLoader(self.next_train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        self.train_set = RevlogDataset(train_set)\n",
    "        sampler = RevlogSampler(self.train_set, batch_size=self.batch_size)\n",
    "        self.train_data_loader = DataLoader(self.train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        self.test_set = RevlogDataset(test_set)\n",
    "        sampler = RevlogSampler(self.test_set, batch_size=self.batch_size)\n",
    "        self.test_data_loader = DataLoader(self.test_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "        print(\"dataset built\")\n",
    "\n",
    "    def train(self, verbose: bool=True):\n",
    "        # pretrain\n",
    "        best_loss = np.inf\n",
    "        weighted_loss, w = self.eval()\n",
    "        if weighted_loss < best_loss:\n",
    "            best_loss = weighted_loss\n",
    "            best_w = w\n",
    "\n",
    "        pbar = tqdm(desc=\"pre-train\", colour=\"red\", total=len(self.pre_train_data_loader) * self.n_epoch)\n",
    "        for k in range(self.n_epoch):\n",
    "            for i, batch in enumerate(self.pre_train_data_loader):\n",
    "                self.model.train()\n",
    "                self.optimizer.zero_grad()\n",
    "                sequences, delta_ts, labels, seq_lens = batch\n",
    "                real_batch_size = seq_lens.shape[0]\n",
    "                outputs, _ = self.model(sequences)\n",
    "                stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "                retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "                loss = self.loss_fn(retentions, labels)\n",
    "                loss.backward()\n",
    "                self.optimizer.step()\n",
    "                self.model.apply(self.clipper)\n",
    "                pbar.update(n=real_batch_size)\n",
    "\n",
    "        pbar.close()\n",
    "        for name, param in self.model.named_parameters():\n",
    "            tqdm.write(f\"{name}: {list(map(lambda x: round(float(x), 4),param))}\")\n",
    "\n",
    "        epoch_len = len(self.next_train_data_loader)\n",
    "        pbar = tqdm(desc=\"train\", colour=\"red\", total=epoch_len*self.n_epoch)\n",
    "        print_len = max(self.batch_nums*self.n_epoch // 10, 1)\n",
    "        for k in range(self.n_epoch):\n",
    "            weighted_loss, w = self.eval()\n",
    "            if weighted_loss < best_loss:\n",
    "                best_loss = weighted_loss\n",
    "                best_w = w\n",
    "\n",
    "            for i, batch in enumerate(self.next_train_data_loader):\n",
    "                self.model.train()\n",
    "                self.optimizer.zero_grad()\n",
    "                sequences, delta_ts, labels, seq_lens = batch\n",
    "                real_batch_size = seq_lens.shape[0]\n",
    "                outputs, _ = self.model(sequences)\n",
    "                stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "                retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "                loss = self.loss_fn(retentions, labels)\n",
    "                loss.backward()\n",
    "                for param in self.model.parameters():\n",
    "                    param.grad[:2] = torch.zeros(2)\n",
    "                self.optimizer.step()\n",
    "                self.scheduler.step()\n",
    "                self.model.apply(self.clipper)\n",
    "                pbar.update(real_batch_size)\n",
    "\n",
    "                if verbose and (k * self.batch_nums + i + 1) % print_len == 0:\n",
    "                    tqdm.write(f\"iteration: {k * epoch_len + (i + 1) * self.batch_size}\")\n",
    "                    for name, param in self.model.named_parameters():\n",
    "                        tqdm.write(f\"{name}: {list(map(lambda x: round(float(x), 4),param))}\")\n",
    "        pbar.close()\n",
    "\n",
    "        weighted_loss, w = self.eval()\n",
    "        if weighted_loss < best_loss:\n",
    "            best_loss = weighted_loss\n",
    "            best_w = w\n",
    "\n",
    "        return best_w\n",
    "\n",
    "    def eval(self):\n",
    "        self.model.eval()\n",
    "        with torch.no_grad():\n",
    "            sequences, delta_ts, labels, seq_lens = self.train_set.x_train, self.train_set.t_train, self.train_set.y_train, self.train_set.seq_len\n",
    "            real_batch_size = seq_lens.shape[0]\n",
    "            outputs, _ = self.model(sequences.transpose(0, 1))\n",
    "            stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "            retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "            tran_loss = self.loss_fn(retentions, labels)/len(self.train_set)\n",
    "            self.avg_train_losses.append(tran_loss)\n",
    "            tqdm.write(f\"Loss in trainset: {tran_loss:.4f}\")\n",
    "\n",
    "            sequences, delta_ts, labels, seq_lens = self.test_set.x_train, self.test_set.t_train, self.test_set.y_train, self.test_set.seq_len\n",
    "            real_batch_size = seq_lens.shape[0]\n",
    "            outputs, _ = self.model(sequences.transpose(0, 1))\n",
    "            stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "            retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "            test_loss = self.loss_fn(retentions, labels)/len(self.test_set)\n",
    "            self.avg_eval_losses.append(test_loss)\n",
    "            tqdm.write(f\"Loss in testset: {test_loss:.4f}\")\n",
    "\n",
    "            w = list(map(lambda x: round(float(x), 4), dict(self.model.named_parameters())['w'].data))\n",
    "\n",
    "            weighted_loss = (tran_loss * len(self.train_set) + test_loss * len(self.test_set)) / (len(self.train_set) + len(self.test_set))\n",
    "\n",
    "            return weighted_loss, w\n",
    "\n",
    "    def plot(self):\n",
    "        fig = plt.figure()\n",
    "        ax = fig.gca()\n",
    "        ax.plot(self.avg_train_losses, label='train')\n",
    "        ax.plot(self.avg_eval_losses, label='test')\n",
    "        ax.set_xlabel('epoch')\n",
    "        ax.set_ylabel('loss')\n",
    "        ax.legend()\n",
    "        return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a05b2762e6fb433b96b8783e997d08fb",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/88151 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensorized!\n",
      "TRAIN: 57372 TEST: 30779\n",
      "dataset built\n",
      "Loss in trainset: 0.3326\n",
      "Loss in testset: 0.3111\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bef605b44a4c44b1923312b576eb348f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/15276 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [1.2588, 1.8518, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0, 0.8, 1.2]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "334fcdcb6a1f46cd97f7e4e04049ba23",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156840 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3301\n",
      "Loss in testset: 0.3088\n",
      "iteration: 15360\n",
      "w: [1.2327, 2.0554, 5.1704, -1.2888, -1.0631, 0.05, 1.5127, -0.15, 0.9225, 2.0657, -0.1538, 0.3585, 0.9266, 0.01, 1.8273]\n",
      "iteration: 30720\n",
      "w: [1.2313, 2.0664, 5.199, -1.6744, -1.1788, 0.05, 1.5602, -0.15, 0.9677, 2.0623, -0.181, 0.2899, 0.9052, 0.01, 1.996]\n",
      "iteration: 46080\n",
      "w: [1.2312, 2.067, 5.1731, -1.7117, -1.2651, 0.05, 1.5212, -0.1653, 0.9408, 2.0769, -0.1803, 0.3416, 0.8938, 0.01, 2.2843]\n",
      "Loss in trainset: 0.3130\n",
      "Loss in testset: 0.2944\n",
      "iteration: 60984\n",
      "w: [1.2312, 2.067, 5.1632, -1.8159, -1.281, 0.05, 1.5004, -0.2059, 0.9203, 2.0056, -0.2582, 0.3222, 0.8462, 0.01, 2.2612]\n",
      "iteration: 76344\n",
      "w: [1.2312, 2.067, 5.0686, -1.7852, -1.2661, 0.05, 1.5376, -0.15, 0.9542, 2.0196, -0.2448, 0.2615, 0.8069, 0.01, 2.2091]\n",
      "iteration: 91704\n",
      "w: [1.2312, 2.067, 5.1225, -1.848, -1.2942, 0.05, 1.4901, -0.204, 0.9109, 2.0634, -0.2057, 0.2774, 0.77, 0.01, 2.3249]\n",
      "Loss in trainset: 0.3131\n",
      "Loss in testset: 0.2943\n",
      "iteration: 106608\n",
      "w: [1.2312, 2.067, 5.0615, -1.8093, -1.2705, 0.05, 1.5123, -0.1725, 0.9279, 2.0367, -0.2354, 0.3221, 0.6855, 0.01, 2.3063]\n",
      "iteration: 121968\n",
      "w: [1.2312, 2.067, 5.0664, -1.7981, -1.2912, 0.05, 1.4962, -0.1751, 0.9104, 2.0589, -0.2129, 0.3398, 0.6707, 0.01, 2.3191]\n",
      "iteration: 137328\n",
      "w: [1.2312, 2.067, 5.0666, -1.8107, -1.2962, 0.05, 1.4975, -0.1618, 0.9101, 2.0518, -0.2207, 0.3451, 0.6622, 0.01, 2.3063]\n",
      "iteration: 152688\n",
      "w: [1.2312, 2.067, 5.0693, -1.8104, -1.2988, 0.05, 1.4918, -0.1682, 0.9043, 2.0471, -0.2254, 0.3406, 0.6578, 0.01, 2.3021]\n",
      "Loss in trainset: 0.3128\n",
      "Loss in testset: 0.2941\n",
      "TRAIN: 59696 TEST: 28455\n",
      "dataset built\n",
      "Loss in trainset: 0.3188\n",
      "Loss in testset: 0.3382\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1473e7e9aad647b383bb54b6cd3a24f5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/22374 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [2.0143, 2.047, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0, 0.8, 1.2]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "dbfedbc1da394693a6f2a61066762484",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156714 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3158\n",
      "Loss in testset: 0.3366\n",
      "iteration: 15360\n",
      "w: [2.1098, 2.1547, 5.0869, -1.2348, -1.0989, 0.05, 1.5737, -0.15, 0.9975, 2.01, -0.2098, 0.2066, 1.1471, 0.0369, 1.9268]\n",
      "iteration: 30720\n",
      "w: [2.1147, 2.1603, 5.0993, -1.6721, -1.1608, 0.05, 1.5334, -0.1642, 0.9987, 2.0167, -0.225, 0.3561, 1.0925, 0.0232, 1.9206]\n",
      "iteration: 46080\n",
      "w: [2.1149, 2.1605, 5.0491, -1.925, -1.0795, 0.05, 1.4569, -0.1631, 0.9456, 1.9739, -0.2775, 0.3316, 0.9141, 0.01, 2.0785]\n",
      "Loss in trainset: 0.3003\n",
      "Loss in testset: 0.3208\n",
      "iteration: 60942\n",
      "w: [2.1149, 2.1605, 4.9807, -1.8318, -1.005, 0.0606, 1.3733, -0.1782, 0.8678, 2.003, -0.2501, 0.3294, 0.9018, 0.01, 2.1234]\n",
      "iteration: 76302\n",
      "w: [2.1149, 2.1605, 4.8911, -1.7637, -0.9144, 0.05, 1.3516, -0.1721, 0.852, 1.9857, -0.2678, 0.3534, 0.7797, 0.01, 2.0631]\n",
      "iteration: 91662\n",
      "w: [2.1149, 2.1605, 4.8401, -1.7311, -0.9873, 0.05, 1.3972, -0.15, 0.8943, 1.9943, -0.261, 0.3383, 0.7377, 0.01, 2.151]\n",
      "Loss in trainset: 0.2996\n",
      "Loss in testset: 0.3202\n",
      "iteration: 106524\n",
      "w: [2.1149, 2.1605, 4.8536, -1.7399, -1.0516, 0.05, 1.3913, -0.1637, 0.8828, 2.0166, -0.2359, 0.3528, 0.7298, 0.01, 2.1698]\n",
      "iteration: 121884\n",
      "w: [2.1149, 2.1605, 4.8496, -1.7404, -1.0639, 0.05, 1.392, -0.1509, 0.8818, 2.0176, -0.2337, 0.3451, 0.7019, 0.01, 2.1818]\n",
      "iteration: 137244\n",
      "w: [2.1149, 2.1605, 4.8557, -1.7555, -1.0602, 0.05, 1.3813, -0.1554, 0.8701, 2.0236, -0.2267, 0.3507, 0.7021, 0.01, 2.1579]\n",
      "iteration: 152604\n",
      "w: [2.1149, 2.1605, 4.8557, -1.7541, -1.0613, 0.05, 1.3791, -0.1577, 0.8676, 2.0217, -0.2283, 0.3492, 0.6989, 0.01, 2.1575]\n",
      "Loss in trainset: 0.2996\n",
      "Loss in testset: 0.3201\n",
      "TRAIN: 59234 TEST: 28917\n",
      "dataset built\n",
      "Loss in trainset: 0.3241\n",
      "Loss in testset: 0.3270\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "52ce61d5248545c8a42a230ced32e515",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/20916 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [1.2804, 1.8287, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0, 0.8, 1.2]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "eae4260855774682b3bf7a6b3fa82f4f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156786 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3220\n",
      "Loss in testset: 0.3242\n",
      "iteration: 15360\n",
      "w: [1.2103, 1.9125, 5.132, -1.2891, -1.1466, 0.05, 1.5503, -0.1688, 0.9875, 2.0283, -0.1655, 0.3399, 1.0614, 0.01, 1.7532]\n",
      "iteration: 30720\n",
      "w: [1.2066, 1.9168, 5.1539, -1.589, -1.1787, 0.05, 1.456, -0.1725, 0.9221, 1.9261, -0.2676, 0.3247, 0.6889, 0.01, 1.7572]\n",
      "iteration: 46080\n",
      "w: [1.2065, 1.917, 5.0463, -1.6385, -1.0992, 0.05, 1.4455, -0.1544, 0.9055, 1.9737, -0.2257, 0.3337, 0.4831, 0.0481, 2.0026]\n",
      "Loss in trainset: 0.3062\n",
      "Loss in testset: 0.3070\n",
      "iteration: 60966\n",
      "w: [1.2065, 1.917, 5.0339, -1.6272, -1.2873, 0.05, 1.4519, -0.1698, 0.9049, 2.0089, -0.2013, 0.3612, 0.3752, 0.01, 2.2173]\n",
      "iteration: 76326\n",
      "w: [1.2065, 1.917, 5.0123, -1.6341, -1.3128, 0.05, 1.4221, -0.1856, 0.8717, 2.0003, -0.209, 0.336, 0.3401, 0.01, 2.1615]\n",
      "iteration: 91686\n",
      "w: [1.2065, 1.917, 4.9573, -1.7079, -1.305, 0.05, 1.4894, -0.15, 0.9332, 2.0288, -0.1732, 0.3299, 0.3067, 0.01, 2.1204]\n",
      "Loss in trainset: 0.3062\n",
      "Loss in testset: 0.3070\n",
      "iteration: 106572\n",
      "w: [1.2065, 1.917, 4.9513, -1.7472, -1.2989, 0.0502, 1.4898, -0.153, 0.9313, 2.0207, -0.1808, 0.3319, 0.2516, 0.0382, 2.1351]\n",
      "iteration: 121932\n",
      "w: [1.2065, 1.917, 4.9496, -1.7574, -1.3096, 0.05, 1.4761, -0.1751, 0.9161, 2.0124, -0.1883, 0.3365, 0.2184, 0.0132, 2.0991]\n",
      "iteration: 137292\n",
      "w: [1.2065, 1.917, 4.9644, -1.7813, -1.3206, 0.05, 1.4665, -0.1786, 0.9058, 2.0184, -0.1814, 0.3432, 0.2155, 0.01, 2.1014]\n",
      "iteration: 152652\n",
      "w: [1.2065, 1.917, 4.964, -1.7808, -1.3213, 0.05, 1.4645, -0.1795, 0.9036, 2.0162, -0.1837, 0.3428, 0.2146, 0.01, 2.1009]\n",
      "Loss in trainset: 0.3061\n",
      "Loss in testset: 0.3069\n",
      "\n",
      "Training finished!\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAkgAAAGwCAYAAABSN5pGAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAABYaElEQVR4nO3deXRU9f3/8edM9pCNhJCwBAIEgbCFEEDABcum4i4VlV2o7delKrZVa6tWq1HrVpVaf7UCglatoHVlEQUFI0tC2PctbElYE5JAlpn7++MmIQkJmYTMTCZ5Pc6Zw829n3vnfZmmvLzzue9rMQzDQERERETKWd1dgIiIiEhjo4AkIiIiUoUCkoiIiEgVCkgiIiIiVSggiYiIiFShgCQiIiJShQKSiIiISBXe7i7AU9ntdg4fPkxwcDAWi8Xd5YiIiIgDDMPg9OnTtG3bFqu15utECkj1dPjwYWJiYtxdhoiIiNTDgQMHaN++fY3bFZDqKTg4GDD/gkNCQtxcjYiIiDgiNzeXmJiY8n/Ha6KAVE9lX6uFhIQoIImIiHiY2qbHaJK2iIiISBUKSCIiIiJVKCCJiIiIVKE5SCIiIo2MzWajuLjY3WV4JB8fH7y8vC76OApIIiIijYRhGGRmZnLq1Cl3l+LRwsLCiI6Ovqg+hQpIIiIijURZOGrdujWBgYFqRFxHhmFQUFBAdnY2AG3atKn3sRSQREREGgGbzVYejiIiItxdjscKCAgAIDs7m9atW9f76zZN0hYREWkEyuYcBQYGurkSz1f2d3gx87gUkERERBoRfa128Rri71ABSURERKQKBSQRERGRKhSQREREpNGIjY3ltddec3cZuout0Tmxx/wzvLN76xAREXHQsGHDSEhIaJBgs2bNGlq0aHHxRV0kXUFqbJa9AK/3gznXw8ZPoPisuysSERG5KIZhUFJS4tDYyMjIRnEnnwJSY2IYUJQHWGDvDzB/GrzSHb55FLK2uLs6ERFxMcMwKCgqccvLMAyHapwyZQrLly/n73//OxaLBYvFwuzZs7FYLHzzzTf0798fPz8/VqxYwe7du7nxxhuJiooiKCiIAQMG8O2331Y6XtWv2CwWC++88w4333wzgYGBdO3alc8//7wh/5qrpa/YGhOLBW5/H05lwLr3Yd08yD0Iq94yX+2SIHES9LoF/ILdXa2IiDjZmWIb8U8scst7b3l6NIG+tceEv//97+zYsYNevXrx9NNPA7B582YAHn30UV566SU6d+5My5YtOXDgANdeey3PPvssfn5+vPfee1x//fVs376dDh061Pgef/nLX3jxxRf529/+xhtvvMH48ePZv38/4eHhDXOy1dAVpMYorANc9Rg8uAHGz4ceN4DVGw6thS9+Cy91g//dBwfXmledRERE3CQ0NBRfX18CAwOJjo4mOjq6vHv1008/zciRI+nSpQvh4eH07duXX//61/Tq1YuuXbvyzDPP0KVLl1qvCE2ZMoU77riDuLg4nnvuOfLy8li9erVTz0tXkBozqxd0HWG+8rJh/YeQ9h4c3wnr5pqv1vHmVaU+4yDQeUlaRERcL8DHiy1Pj3bbe1+spKSkSj/n5eXx1FNP8dVXX3HkyBFKSko4c+YMGRkZFzxOnz59ypdbtGhBSEhI+fPWnEUByVMEtYahv4Uh90NGihmUNn8G2Vtg4aOw5Anocb0ZlmKvAKsuDoqIeDqLxeLQ11yNVdW70X73u9+xZMkSXnrpJeLi4ggICGDs2LEUFRVd8Dg+Pj6VfrZYLNjt9gavtyLP/VtvriwW6DjEfF39PGz6xAxLR9bDpvnmq2Us9JsICeMhpP5PMhYREXGEr68vNput1nErV65kypQp3HzzzYB5RWnfvn1Orq5+dJnBkwWEwYDp8Osf4O7lkDQN/ELg5D747hl4NR4+uB22fQ02x26vFBERqavY2FhWrVrFvn37OHbsWI1Xd7p27cqCBQtIT09n/fr13HnnnU6/ElRfCkhNRdsEuO4VeHg73PRP6DAEDDvs+AY+vANe7Qnf/uVcI0oREZEG8rvf/Q4vLy/i4+OJjIyscU7RK6+8QsuWLRkyZAjXX389o0ePJjEx0cXVOsZiONroQCrJzc0lNDSUnJwcQkJC3F1O9Y7tNL9+S/8ACo6dWx97OfSfAt2vAx9/t5UnIiLnnD17lr1799KpUyf8/fX/zRfjQn+Xjv77rTlITVmrrjDqGfjFn2HHQjMs7foW9v1ovvzDoO/t5sTuqJ7urlZERKTRUEBqDrx9If4G83XqAKSXNqHMOQCr/mm+2vUvbUJ5q5pQiohIs6c5SM1NWAwMexQeWA8T5kP8jWD1gUOp8MUDpU0o74UDq9WEUkREmi1dQWqurF4QN8J85R2FDR9C6pzSJpTzzFdkj3NNKFtEuLtiERERl9EVJIGgSLMB5X1rYOpC6HsneAfA0a2w6DHzgbn/nQq7v4dGejumiIhIQ9IVJDnHYoGOg83XNc/DxrImlOmweYH5CusA/SZBwp0Q2s7dFYuIiDiFriBJ9fxDYcA0+PVysxHlgF+BXyicyoDv/wqv9YIPxsG2r8BW7O5qRUREGpSuIEnt2vSFMX1h5NOw9XPzqtL+lWbrgB0LISjKvKLUbyJEdHF3tSIiIhdNV5DEcb6BZt+kqV/DfWth6APQIhLysmDFq/BGIsy+DjZ8DMVn3V2tiIhIvSkgSf206mpeUZqxFcbNg7iRgMVsQLngV/ByN/j6D5C5yd2VioiIkw0bNowHH3ywwY43ZcoUbrrppgY7Xn3oKza5OF4+0ON685VzENa9D+vmmk0oV79tvtomnmtC6d9IH8siIiJSga4gScMJbQ/DHiltQrkA4m8ym1AeToMvHzSvKn12L2SsUhNKEZEmYsqUKSxfvpy///3vWCwWLBYL+/btY9OmTVxzzTUEBQURFRXFxIkTOXbs3HNBP/nkE3r37k1AQAARERGMGDGC/Px8nnrqKebMmcP//ve/8uMtW7bM5eelh9XWk0c8rLYxyD8G6z+EtDlwbMe59ZHdS5tQ3q4mlCIi1PCAVcOA4gL3FOQTaLZ/qUVOTg7XXHMNvXr14umnnzZ39fGhR48eTJ8+nUmTJnHmzBkeeeQRSkpK+O677zhy5AgdOnTgxRdf5Oabb+b06dP8+OOPTJo0CYBp06aRm5vLrFmzAAgPD8fX19fh0vWwWmn8WrSCIffB4HvhwCrzDrhNC+DoNlj0R1jyJPS4zgxLnYaBVRc1RUTKFRfAc23d895/PAy+LWodFhoaiq+vL4GBgURHRwPw17/+lX79+vHcc8+Vj3v33XeJiYlhx44d5OXlUVJSwi233ELHjh0B6N27d/nYgIAACgsLy4/nDgpI4hoWC3S41HxdnQyb5pth6fA62Pyp+QrrYLYKSBivJpQiIh5s/fr1fP/99wQFBZ23bffu3YwaNYrhw4fTu3dvRo8ezahRoxg7diwtW7Z0Q7XVU0AS1/MPhaS7zNeRDWZQ2vBxaRPKZ2FZsnlXXOIkuGS0ORFcRKQ58gk0r+S4673rKS8vj+uvv54XXnjhvG1t2rTBy8uLJUuW8NNPP7F48WLeeOMNHn/8cVatWkWnTp0upuoGo4Ak7tWmD4x5CUY9A1vKmlCugJ2LzFeL1mYTysRJakIpIs2PxeLQ11zu5uvri81mK/85MTGR+fPnExsbi7d39VHDYrEwdOhQhg4dyhNPPEHHjh359NNPmTFjxnnHcwdN+JDGwScA+o6DqV/Bfakw9EEzHOVnw8rXzCaUs8bA+o+g+Iy7qxURkQpiY2NZtWoV+/bt49ixY9x7772cOHGCO+64gzVr1rB7924WLVrE1KlTsdlsrFq1iueee461a9eSkZHBggULOHr0KD169Cg/3oYNG9i+fTvHjh2juNj1j7RSQJLGp1UcjPwLzNgC496HrqPBYjWvLH16d2kTyt9D5kZ3VyoiIsDvfvc7vLy8iI+PJzIykqKiIlauXInNZmPUqFH07t2bBx98kLCwMKxWKyEhIfzwww9ce+21XHLJJfzpT3/i5Zdf5pprrgHgV7/6Fd26dSMpKYnIyEhWrlzp8nNqFLf5z5w5k7/97W9kZmbSt29f3njjDQYOHFjt2AULFvDcc8+xa9cuiouL6dq1Kw8//DATJ04EoLi4mD/96U98/fXX7Nmzh9DQUEaMGMHzzz9P27bn7gSIjY1l//79lY6dnJzMo48+6lDNus3fxXIOQvoHkDYXcjLOrW/br7QJ5Vg1oRQRj3ahW9OlbhriNn+3X0H66KOPmDFjBk8++SRpaWn07duX0aNHk52dXe348PBwHn/8cVJSUtiwYQNTp05l6tSpLFq0CICCggLS0tL485//TFpaGgsWLGD79u3ccMMN5x3r6aef5siRI+Wv+++/36nnKhchtD1c+QezCeXET6HnzaVNKNfBlw+VNqG8BzJ+VhNKERG5aG6/gjRo0CAGDBjAm2++CYDdbicmJob777/f4as5iYmJjBkzhmeeeaba7WvWrGHgwIHs37+fDh06AOYVpAcffLDez47RFaRGoLwJ5XtwbPu59a0uMa8q9b3D7MMkIuIBdAWp4Xj8FaSioiJSU1MZMWJE+Tqr1cqIESNISUmpdX/DMFi6dCnbt2/niiuuqHFcTk4OFouFsLCwSuuff/55IiIi6NevH3/7298oKSmp8RiFhYXk5uZWeomblTWhvHcV3LUYEiaYt6Ue2wGL/wQvd4ePJ8OupWC3u7taERHxIG69zf/YsWPYbDaioqIqrY+KimLbtm017peTk0O7du0oLCzEy8uLf/zjH4wcObLasWfPnuWRRx7hjjvuqJQUf/vb35KYmEh4eDg//fQTjz32GEeOHOGVV16p9jjJycn85S9/qcdZitNZLNBhkPmq1IQyDbZ8Zr5CO0C/CdBvvPl1nYiIyAV4ZB+k4OBg0tPTycvLY+nSpcyYMYPOnTszbNiwSuOKi4u57bbbMAyDt956q9K2GTNmlC/36dMHX19ffv3rX5OcnIyfn9957/nYY49V2ic3N5eYmJiGPTG5eP4hkDTVfGVuNCd1b/jQnNi97DlY/jzEjShtQnm1mlCKSKPTCO6d8ngN8Xfo1oDUqlUrvLy8yMrKqrQ+Kyvrgs9fsVqtxMXFAZCQkMDWrVtJTk6uFJDKwtH+/fv57rvvap0nNGjQIEpKSti3bx/dunU7b7ufn1+1wUkasejecO2LZsuArV+YV5X2/Qg7F5uvFpFmE8p+k8zWAiIibuTjY/4HW0FBAQEBAW6uxrMVFJgP+C37O60PtwYkX19f+vfvz9KlS7npppsAc5L20qVLue+++xw+jt1up7CwsPznsnC0c+dOvv/+eyIian9afHp6OlarldatW9f5PKSR8wmAPreZr+O7Yd1cWPd+aRPKv5uvjkPNq0o9bgDf+rfXFxGpLy8vL8LCwsrv4g4MDMRisbi5Ks9iGAYFBQVkZ2cTFhaGl5dXvY/l9q/YZsyYweTJk0lKSmLgwIG89tpr5OfnM3XqVAAmTZpEu3btSE5OBsy5QElJSXTp0oXCwkK+/vpr5s6dW/4VWnFxMWPHjiUtLY0vv/wSm81GZmYmYLYI8PX1JSUlhVWrVnHVVVcRHBxMSkoKDz30EBMmTGhUD8oTJ4joAiOegqseN68ipc6BXUtg/0rz9fUfoM8vIXGy+RgUEREXKvv2pKZWN+KYsLCwC34T5Qi3B6Rx48Zx9OhRnnjiCTIzM0lISGDhwoXlE7czMjKwWs/dbJefn88999zDwYMHCQgIoHv37sybN49x48YBcOjQIT7//HPA/Pqtou+//55hw4bh5+fHhx9+yFNPPUVhYSGdOnXioYceqjTHSJo4Lx/oPsZ85Rwym1Cue898YO6ad8xXmwTzqlLvseYDdkVEnMxisdCmTRtat27tlsdrNAU+Pj4XdeWojNv7IHkq9UFqgux22LvcnKu07UuwFZnrvQPMxpSJk6DDpeZdcyIi4pEc/fdbAameFJCauPzjsOEjSJsDRyu0nChrQtnndgiKdF99IiJSLwpITqaA1EwYBhxcYwalTQug2LwzAqsPdL/WDEudrwLrxV/OFRER51NAcjIFpGbobC5sXmB+BXco9dz60BizCWXCeAhTbywRkcZMAcnJFJCaucxNZlDa8CGczSldaYG44eYdcJdcDd6+bi1RRETOp4DkZApIAkDxGdj6pfkV3L4fz62P6gXTvzV7MImISKPhEQ+rlfMt3pzJrJV7OXiywN2liCN8Asy+SVO+hPvT4LIZ4BcKWZtg86furk5EROrJ7X2QpLI5KftYues4f/liCz3bhjAqPppRPaPoHh2sjqqNXUQXGPEk+AXB0qdh7SzzUSYiIuJxFJAamZE9oii2Gazdd4LNh3PZfDiXV7/dQUx4AKPioxkZH0VSx5Z4e+niX6OVMAG+fw4OrjYfmBvd290ViYhIHWkOUj05ew7S8bxClm7LZvHmLH7ceZTCEnv5tpaBPgzvEcWo+Cgu7xpJgK9uMW90Pp4MWz6DpGlw3SvurkZEREppkraTuXKSdkFRCT/uPMbizVks3ZbFqYJz7ef9faxc0TWSUT2jGd69NS1b6M6pRmHPcnjvBvANhoe3mV+7iYiI2ykgOZm77mIrsdlZs+8ki7dksnhzFodOnSnfZrXAwE7hjIyPZlR8FDHheiq92xgGvJkEx3fB9X+H/lPcXZGIiKCA5HSN4TZ/wzDYciSXxZuzWLIliy1Hcitt79EmhFHxUYzqGUV8mxBN8na1n96AxX+C6D7w6x/0DDcRkUZAAcnJGkNAqurAiQKWbMli8ZZMVu89gb3CJ9suLIBRPaMYFR/NgFhN8naJ/OPwSg+wFcKvvoN2/d1dkYhIs6eA5GSNMSBVdCK/iO+2ZbN4cyY/7DzK2eJzk7zDAn34RffWjIqP5opLWhHoq5sZnWbB3eZDb/tNhBvfdHc1IiLNngKSkzX2gFTRmSIbP+48ypItWXy7NYuTFSZ5+3lbubxrJKN6RjG8e2sigvzcWGkTtD8FZl0NPoEwYysEhLm7IhGRZk0Byck8KSBVVGKzk7r/JIu3ZLFocyYHT1ae5J0UG27OW4qPpkOEJnlfNMOAfwyGo1vhmr/BoLvdXZGISLOmgORknhqQKjIMg22Zp1m82Zy3tPlw5Une3aODGdXTvCOuZ1tN8q63Vf8Pvvk9tI6H//tJk7VFRNxIAcnJmkJAqurgyQK+3ZLF4i1ZrNp7AluFWd7twgIYGW82pxzQKRwfTfJ23JlT8HJ3KDkDdy2CDpe6uyIRkWZLAcnJmmJAquhUQdkk7yyW7zjKmWJb+bbQAB+Gd2/NqJ5RXHFJpCZ5O+J/98K6edBnHNzy/9xdjYhIs6WA5GRNPSBVdLbYxoqdx1i8JZNvt2ZzIr+ofJs5ybsVI+OjGN4jilaa5F29Q6nwr1+Al5/ZWTsw3N0ViYg0SwpITtacAlJFNrtBWsZJFm/OZNHmLDJOFJRvs1ggqWPL8ofqxrZq4cZKGxnDgLevgMwNMOpZGHKfuysSEWmWFJCcrLkGpIoMw2BHVh6LN2eyeEsWGw/lVNreLSq4vDllr3aa5M3aWfDlgxARB/et1WRtERE3UEByMgWk8x06daZ0kncmq/acoKTCJO82of6lk7yjGdS5mU7yLjwNL/eAotMw+QvodIW7KxIRaXYUkJxMAenCcgqK+X57Nou3ZLJs+1EKis5N8g7x9zY7efeM5opLIgnya0aTvL98CNa+Cz1vhl/Odnc1IiLNjgKSkykgOe5ssY2fdh9j8Wazk/exvHOTvH29rVwW14pRpZO8I4Ob+CTvzI3wz8vA6m121g5q7e6KRESaFQUkJ1NAqh+b3WBdhtnJe/HmTPYdrzzJO7FDS7OTd89oOjXVSd7vjICDa2D4k3D5DHdXIyLSrCggOZkC0sUzDINd2XnlYWn9wcqTvLu2Diqf5N27XShWaxOZ1LzuffjfPRDWAX67HqzNcD6WiIibKCA5mQJSwzuSc6a8k3fK7uOVJnlHh5iTvEfGR3Fp5wh8vT04VBQVwCvd4WwOjJ8PXUe4uyIRkWZDAcnJFJCcK+dMMcu2m528l23PJr/CJO9gP2+uKu3kfeUlkQT7+7ix0nr65lFY9RZ0vw5uf9/d1YiINBsKSE6mgOQ6hSU2ftp9nMWbs1iyJYtjeYXl23y9rAyJi2BUfDQj4lvTOtjfjZXWwdHtMHMgWLzgwY0Q2s7dFYmINAsKSE6mgOQedrvBugOnWLwlk8Wbs9h7LL98m8UC/WLCGBkfzaieUXSJDHJjpQ6YdS3sXwnDHoNhj7q7GhGRZkEByckUkNzPMAx2H81jUemVpfQDpypt7xLZglE9oxkVH0Xf9mGNb5L3xk9g/jQIaQcPbACvZtQPSkTETRSQnEwBqfHJyj3LkvJJ3scotp37n3brYD+zk3fPaAY3lkneJYXwSg8oOA63/we6X+vuikREmjwFJCdTQGrccs8Ws2z7URZvNjt55xWWlG8L9vPmym6RjOoZzbBukYS4c5L34j/DT69D3EiY8In76hARaSYUkJxMAclzFJbYSNl9nCVbzK/isk+fm+Tt42VhcBezk/fI+CiiQlw8yfv4bngjEbDAA+uhZUfXvr+ISDOjgORkCkieyW43WH/wVHlzyt1H8yttT4gJK29OGdfaRZO837sJ9nwPlz8Mw59wzXuKiDRTCkhOpoDUNOzKziudt5TJuoxTlbZ1btWCkaVhqV+MEyd5b/kffDwJWrSGhzaDt69z3kdERBSQnE0BqenJzj3Lt1uzWbwlk592HafIZi/fFhnsx4geUYzqGcWQLhH4eXs13BvbiuHVnpCXBb+cDT1vbrhji4hIJQpITqaA1LSdPlvM8h1HWbw5i++3ZXO6wiTvFr5eDOvemlHxUQzr1prQgAaY5P3dX+GHv0GnK2Hy5xd/PBERqZYCkpMpIDUfRSV2ft5znMVbMlmyJYus3HOTvL2tFgZ3iSid5B1NdGg9J3mfyoDX+gAG3JcKreIapngREalEAcnJFJCaJ7vdYMOhHJaUdvLemZ1XaXvf9qGM6hnNjQltad8ysG4Hf/822LkIBt8Ho59twKpFRKSMApKTKSAJwJ6jeeXNKdMyTlL22xQW6MOSh64kMtjP8YNtXwj/GQcB4TBjK/h4yHPlREQ8iKP/fjeCdsIinqtzZBC/vrIL8/9vCKv+OJzkW3oTGxHIqYJi5v68v24H6zoSQtrDmROwVfOQRETcSQFJpIG0DvbnjoEd+MPV3QGY9/N+zhbbHD+A1Qv6TzaX177rhApFRMRRCkgiDWxUfBTtWwZwIr+IT9cdqtvO/SaCxQsyUiB7q3MKFBGRWikgiTQwby8rU4d2AuCdH/dgt9dhml9IG+h2jbm8dpYTqhMREUcoIIk4wW1J7Qn282b30XyW7zhat52T7jL/XP8hFBU0fHEiIlIrBSQRJwj29+H2gTEAvLNiT9127nwVtIyFwhzYvKDhixMRkVopIIk4yeQhsXhZLazcdZwth3Md39Fqhf5TzGVN1hYRcQsFJBEnad8ykGt6RQPw7xV767ZzwgSw+sChVDiy3gnViYjIhSggiTjR9Ms7A/D5+kNk5551fMegSIi/wVzWZG0REZdTQBJxooSYMJI6tqTYZvBeSh0bR/afav658b9QeLrhixMRkRopIIk42fTLzVv+563az5miOjSOjL0MIrpCUR5s+NhJ1YmISHUUkEScbGR8NB3CzcePzE876PiOFsu5W/7XzgI9NlFExGUUkESczMtq4a6hsQC8u2Jv3RpH9r0dvPwga6M5YVtERFxCAUnEBX6ZFEOwvzd7juXz3bZsx3cMDIdet5jLuuVfRMRlFJBEXKCFnzd3DuoA1KNxZNnXbJvmw5mTDVyZiIhURwFJxEWmDInF22rh5z0n2HQox/Ed2w+AqF5QchbWf+S8AkVEpJwCkoiLtAkNYEyfNkAdG0daLJU7a2uytoiI0ykgibjQtMvMW/6/WH+YzJw6NI7sMw58WsCx7bD/JydVJyIiZRSQRFyoT/swBnYKp8RuMCdln+M7+odA77Hmcqo6a4uIOJsCkoiLTS+9ivT+z/vJLyxxfMek0s7aW/4H+cecUJmIiJRRQBJxsRE9ooiNCCT3bEndGke27We+bEWQ/r7zChQREQUkEVezWi3lc5HeXbEXW10aR5bd8p86G+z2hi9OREQABSQRt7i1f3tCA3zYd7yApVuzHN+x163gFwIn9sDe5c4rUESkmVNAEnGDQF9vxpc1jvyxDrf8+7Yw72gDddYWEXEiBSQRN5k8JBYfLwur951g/YFTju9YNll7+9dwOtMptYmINHcKSCJuEhXiz/V92gJ1bBwZ1RNiBoG9BNbNdVJ1IiLNmwKSiBvdVTpZ+6uNRzh86ozjO5ZP1p4DdpsTKhMRad4UkETcqFe7UAZ3jsBmN5jz0z7Hd4y/EQJaQs4B2LXUafWJiDRXjSIgzZw5k9jYWPz9/Rk0aBCrV6+uceyCBQtISkoiLCyMFi1akJCQwNy5575mKC4u5pFHHqF37960aNGCtm3bMmnSJA4fPlzpOCdOnGD8+PGEhIQQFhbGtGnTyMvLc9o5itRk+uXmVaQPVmeQ52jjSJ8A6HunuazJ2iIiDc7tAemjjz5ixowZPPnkk6SlpdG3b19Gjx5NdnZ2tePDw8N5/PHHSUlJYcOGDUydOpWpU6eyaNEiAAoKCkhLS+PPf/4zaWlpLFiwgO3bt3PDDTdUOs748ePZvHkzS5Ys4csvv+SHH37g7rvvdvr5ilR1VbfWdI5swemzJfx37QHHdyybrL1zEeTUoeGkiIjUymIY7n00+KBBgxgwYABvvvkmAHa7nZiYGO6//34effRRh46RmJjImDFjeOaZZ6rdvmbNGgYOHMj+/fvp0KEDW7duJT4+njVr1pCUlATAwoULufbaazl48CBt27Y97xiFhYUUFhaW/5ybm0tMTAw5OTmEhITU9bRFKnl/1X4e/3QTMeEBLPvdVXhZLY7tOPs62PcjXPkIXPVH5xYpItIE5ObmEhoaWuu/3269glRUVERqaiojRowoX2e1WhkxYgQpKSm17m8YBkuXLmX79u1cccUVNY7LycnBYrEQFhYGQEpKCmFhYeXhCGDEiBFYrVZWrVpV7TGSk5MJDQ0tf8XExDh4liK1u6Vfe1oG+nDgxBmWbKnDrftlV5FS54Ct2DnFiYg0Q24NSMeOHcNmsxEVFVVpfVRUFJmZNf8jkZOTQ1BQEL6+vowZM4Y33niDkSNHVjv27NmzPPLII9xxxx3lSTEzM5PWrVtXGuft7U14eHiN7/vYY4+Rk5NT/jpwoA5fhYjUIsDXiwmXdgTgX3VpHNn9eghsBXmZsGOhk6oTEWl+3D4HqT6Cg4NJT09nzZo1PPvss8yYMYNly5adN664uJjbbrsNwzB46623Luo9/fz8CAkJqfQSaUgTB3fE18tK6v6TpGWcdGwnb19InGgur53lvOJERJoZtwakVq1a4eXlRVZW5WdRZWVlER0dXeN+VquVuLg4EhISePjhhxk7dizJycmVxpSFo/3797NkyZJKgSY6Ovq8SeAlJSWcOHHigu8r4kytg/25IaEejSMTJ5t/7l4KJ+qwn4iI1MitAcnX15f+/fuzdOm5Pi52u52lS5cyePBgh49jt9srTaAuC0c7d+7k22+/JSIiotL4wYMHc+rUKVJTU8vXfffdd9jtdgYNGnQRZyRycaaVNo78ZuMRDpwocGyn8E7QZbi5nDrbOYWJiDQzbv+KbcaMGfzrX/9izpw5bN26lf/7v/8jPz+fqVPNyaeTJk3iscceKx+fnJzMkiVL2LNnD1u3buXll19m7ty5TJgwATDD0dixY1m7di3vv/8+NpuNzMxMMjMzKSoqAqBHjx5cffXV/OpXv2L16tWsXLmS++67j9tvv73aO9hEXKVHmxAui2uF3aBujSPLOmuvmwclRU6pTUSkOfF2dwHjxo3j6NGjPPHEE2RmZpKQkMDChQvLJ25nZGRgtZ7Lcfn5+dxzzz0cPHiQgIAAunfvzrx58xg3znzC+aFDh/j8888BSEhIqPRe33//PcOGDQPg/fff57777mP48OFYrVZuvfVWXn/9deefsEgtpl3eiRW7jvHhmgM8MKIrwf4+te90ydUQ3AZOH4FtX0CvW51fqIhIE+b2PkieytE+CiJ1ZbcbjHrtB3Zl5/GnMT2Yfnlnx3b8/jlY/gLEXg5TvnRukSIiHsoj+iCJyPmsVgvTS+cizVq5jxKb3bEdEyeBxWo2jjy6w4kViog0fQpIIo3QTf3aEdHCl0OnzrBoc1btOwCEtje/agNN1hYRuUgKSCKNkL/PucaR76zY4/iO/Us7a6e/D8VnnFCZiEjzoIAk0khNuLQjvt5W1mWcInX/Ccd2ihsOoR3g7CnY/JkzyxMRadIUkEQaqchgP25OaAfAO44+fsTqBf1LG0emqrO2iEh9KSCJNGLTLjcnay/anEnGcQcbR/abCFZvOLAKMjc5sToRkaZLAUmkEbskKpgrLonEbsCsnxy8ihQcBd3HmMu6iiQiUi8KSCKNXNkt/x+vOUDOmWLHdirrrL3+IyjMc1JlIiJNlwKSSCN3eddWXBIVRH6RjY/WZDi2U+wVEN4Zik7DpvnOLVBEpAlSQBJp5CwWC9MvM7tpz165j2JHGkdaredu+V/7rhOrExFpmhSQRDzAjf3a0irIj8M5Z/lmU6ZjOyWMBy9fOJIOh9KcWp+ISFOjgCTiAfy8vZg0uLRx5I97cOgRii0iIP5Gc1mTtUVE6kQBScRDjB/UAT9vKxsO5rB2/0nHdiqbrL3xEzib47ziRESaGAUkEQ8REeTHLYntAfjXDw4+fqTDYIjsDsUFsOFjJ1YnItK0KCCJeJBpl8UCsGRrFvuO5de+g8VSYbL2LHDkqzkREVFAEvEkca2DuapbJIYBs1Y62Diy7zjwDoDszXBgtXMLFBFpIhSQRDzM9MvNW/4/XnuQnAIHGkcGtIRet5rLmqwtIuIQBSQRDzOkSwTdo4M5U2zjg9UONo5MKv2abdMCKDjhvOJERJoIBSQRD2OxWMqvIs3+aS9FJQ40jmzXH6J7g60Q1v/HyRWKiHg+BSQRD3RD37a0DvYjK7eQrzceqX0Hi+XcLf+arC0iUisFJBEP5OttZfKQWADeWeFg48jevwTfIDi+E/atcG6BIiIeTgFJxEPdObAD/j5WNh3KZdVeB+YV+QWbIQn0fDYRkVooIIl4qJYtfBnb32wc+c6PDt7yXzZZe+sXkHfUSZWJiHg+BSQRD3bX0E4ALN2WxZ6jebXv0KavOWHbXgzp85xcnYiI51JAEvFgnSODGNGjNYYB7zraOLLiZG27A3fAiYg0QwpIIh5u2mXmLf+fpB7kZH5R7Tv0vAX8QuHUftjznZOrExHxTApIIh7u0s7h9Gwbwtliu2ONI30DIeEOc3mtOmuLiFRHAUnEw5mNI825SLN/2kdhia32ncoeYLv9G8g97MTqREQ8kwKSSBMwpndbokP8OXq6kC/XO9A4snV36DAEDBukzXV+gSIiHkYBSaQJqNw4cq9jjSPLJmunzQFbifOKExHxQApIIk3EnQM7EODjxdYjuaTsPl77DvE3QEA45B6CXUucX6CIiAdRQBJpIkIDfbgtqbRx5AoHbvn39oN+481lddYWEalEAUmkCZk6tBMWC3y3LZtd2Q40jiybrL1zCZxy4A44EZFmQgFJpAmJbdWCkT2iAPi3I1eRIrpApysBA1LnOLc4EREPooAk0sRMv9xsHLkg7SDH8wpr36Fssva6uWArdmJlIiKeQwFJpIkZENuSPu1DKSyx8/4qB7426z4GgqIgLwu2f+38AkVEPIACkkgTY7FYmHaZ2TjyvZR9nC2upXGklw/0m2Aua7K2iAiggCTSJF3buw1tQv05llfE5+sd6JSdOBmwwJ5lcHy3s8sTEWn0FJBEmiAfLytTh8YC8O8fHWgc2bIjdB1pLqfOdmptIiKeoF4Bac6cOXz11VflP//hD38gLCyMIUOGsH///gYrTkTqb9yADrTw9WJ71mlW7DpW+w5lt/yvmwclDkzuFhFpwuoVkJ577jkCAgIASElJYebMmbz44ou0atWKhx56qEELFJH6CQ3w4bYBMQC886MDt/x3HQUh7eDMCdjyuZOrExFp3OoVkA4cOEBcXBwAn332Gbfeeit33303ycnJ/Pjjjw1aoIjU39QhnbBaYPmOo+zIOn3hwV7epXORgNRZzi9ORKQRq1dACgoK4vhx81lPixcvZuRIc+6Cv78/Z86cabjqROSidIgIZHTPaMCci1SrxIlg8YL9KyF7m5OrExFpvOoVkEaOHMn06dOZPn06O3bs4NprrwVg8+bNxMbGNmR9InKRpl9u3vL/afohjp6uZW5RSFvodo25rKtIItKM1SsgzZw5k8GDB3P06FHmz59PREQEAKmpqdxxxx0NWqCIXJzEDi1JiAmjqMTOvJ8duIkiqXSydvp/oKjAucWJiDRSFqPW+3+lOrm5uYSGhpKTk0NISIi7yxG5oC83HOa+D9YR0cKXlY/+An8fr5oH2+3wegKc2g83/gP6jXdZnSIizubov9/1uoK0cOFCVqxYUf7zzJkzSUhI4M477+TkyZP1OaSIONHVPaNpFxbA8fwiPlt36MKDrVboP8VcVmdtEWmm6hWQfv/735ObmwvAxo0befjhh7n22mvZu3cvM2bMaNACReTieVdoHPnOCgcaR/abAFYfOLQWjmxwfoEiIo1MvQLS3r17iY+PB2D+/Plcd911PPfcc8ycOZNvvvmmQQsUkYYxbkAMQX7e7MrOY/mOoxceHNQaelxnLmuytog0Q/UKSL6+vhQUmJM3v/32W0aNGgVAeHh4+ZUlEWlcgv19uL20ceS/Vzhwy3/SXeafGz6Gwlp6KImINDH1CkiXXXYZM2bM4JlnnmH16tWMGTMGgB07dtC+ffsGLVBEGs6UobFYLfDjzmNsy6zlP2ZiL4eIOCjKg43/dU2BIiKNRL0C0ptvvom3tzeffPIJb731Fu3atQPgm2++4eqrr27QAkWk4bRvGcg1vdsADjSOtFjOXUVaOwt0w6uINCO6zb+edJu/eKp1GSe5+R8/4etlZcWjV9E62L/mwQUn4OXuYCuE6d9B+/6uK1RExAmceps/gM1mY/78+fz1r3/lr3/9K59++ik2m62+hxMRF+nXoSX9O7akyGZnbkotjSMDw6HnzeaybvkXkWakXgFp165d9OjRg0mTJrFgwQIWLFjAhAkT6NmzJ7t3727oGkWkgU2/zHz8yLyf93OmqJb/sCn7mm3TfDhzyrmFiYg0EvUKSL/97W/p0qULBw4cIC0tjbS0NDIyMujUqRO//e1vG7pGEWlgo3pGExMewMmCYhasO3jhwTEDoXU8lJyBDR+5pkARETerV0Bavnw5L774IuHh4eXrIiIieP7551m+fHmDFScizuFltTB1iHkV6d8r9mK3X2AqYqXJ2u9qsraINAv1Ckh+fn6cPn1+X5S8vDx8fX0vuigRcb7bBsQQ7O/NnqP5LNuRfeHBfW4Dn0A4ug0yfnZNgSIiblSvgHTddddx9913s2rVKgzDwDAMfv75Z37zm99www03NHSNIuIEQX7e3DmwAwDv1HbLv38o9LrVXNZkbRFpBuoVkF5//XW6dOnC4MGD8ff3x9/fnyFDhhAXF8drr73WwCWKiLNMHhKLl9XCT7uPs/lwzoUHl33NtuUzyD/u9NpERNypXgEpLCyM//3vf+zYsYNPPvmETz75hB07dvDpp58SFhbWwCWKiLO0DQtgTFnjyNoeP9IuEdokgK0I1n/g/OJERNzI4UaRM2bMcPigr7zySr0L8hRqFClNxYaDp7jhzZX4eFlY8cgviAq5QOPI1NnwxQMQ3gXuWwvWerdSExFxC0f//fZ29IDr1q1zaJzFYnH0kCLSCPRpH8bA2HBW7zvBnJ/28Yeru9c8uNdYWPQnOLEb9v0AnYe5rE4REVdyOCB9//33zqxDRNxo2uWdWL3vBO+vyuC+X8QR6FvD/zX4BUHfcbDmHfP5bApIItJE6fq4iDCiRxQdIwLJOVPM/NRaGkf2n2r+ue1LOJ3l/OJERNxAAUlE8LJauGuog40jo3tB+4FgL4F1c11UoYiIaykgiQgAv0xqT2iAD/uOF7B0Wy2NI8tu+U+dA3Y9pFpEmh4FJBEBINDXmzsHlTWO3HPhwT1vAv8wyMmA3d85vTYREVdTQBKRcpMHx+JttbBq7wk2HrxA40ifAEi401xWZ20RaYLcHpBmzpxJbGws/v7+DBo0iNWrV9c4dsGCBSQlJREWFkaLFi1ISEhg7ty5540ZNWoUERERWCwW0tPTzzvOsGHDsFgslV6/+c1vGvrURDxOdKg/1/dtC8C/V9RyFalssvaOhZBTy8RuEREP49aA9NFHHzFjxgyefPJJ0tLS6Nu3L6NHjyY7u/r5D+Hh4Tz++OOkpKSwYcMGpk6dytSpU1m0aFH5mPz8fC677DJeeOGFC773r371K44cOVL+evHFFxv03EQ81bTLzMnaX244wpGcMzUPjLwEOl4Ghh3SNFlbRJoWtwakV155hV/96ldMnTqV+Ph4/vnPfxIYGMi771Z/yX7YsGHcfPPN9OjRgy5duvDAAw/Qp08fVqxYUT5m4sSJPPHEE4wYMeKC7x0YGEh0dHT5S92wRUy92oVyaedwSuwGc37af+HBSaVXkdLmgK3E+cWJiLiI2wJSUVERqamplYKM1WplxIgRpKSk1Lq/YRgsXbqU7du3c8UVV9T5/d9//31atWpFr169eOyxxygoKLjg+MLCQnJzcyu9RJqq6Zd1BuCDVfvJL7xA8OlxPQS2gtNHzK/aRESaCLcFpGPHjmGz2YiKiqq0PioqiszMzBr3y8nJISgoCF9fX8aMGcMbb7zByJEj6/Ted955J/PmzeP777/nscceY+7cuUyYMOGC+yQnJxMaGlr+iomJqdN7iniSX3RvTadWLcg9W8J/1x6oeaC3H/Qbby6nznJNcSIiLuD2Sdp1FRwcTHp6OmvWrOHZZ59lxowZLFu2rE7HuPvuuxk9ejS9e/dm/PjxvPfee3z66afs3r27xn0ee+wxcnJyyl8HDlzgHw0RD2e1WrirdC7Suyv3YbtQ48j+U8w/dy2FE3udX5yIiAu4LSC1atUKLy8vsrIqP6ogKyuL6OjoGvezWq3ExcWRkJDAww8/zNixY0lOTr6oWgYNGgTArl27ahzj5+dHSEhIpZdIUzY2sT1hgT5knChgyZYLPFIkvDN0+QVgmHORRESaALcFJF9fX/r378/SpUvL19ntdpYuXcrgwYMdPo7dbqewsPCiailrBdCmTZuLOo5IUxLg68WEQR0BB275L+usvW4elBQ5uTIREeer4ZHdrjFjxgwmT55MUlISAwcO5LXXXiM/P5+pU807YyZNmkS7du3KrxAlJyeTlJREly5dKCws5Ouvv2bu3Lm89dZb5cc8ceIEGRkZHD58GIDt27cDlN+ttnv3bj744AOuvfZaIiIi2LBhAw899BBXXHEFffr0cfHfgEjjNmlwR97+YTdr9p0k/cApEmLCqh94ydUQFA15meZDbHvd4tI6RUQamlvnII0bN46XXnqJJ554goSEBNLT01m4cGH5xO2MjAyOHDlSPj4/P5977rmHnj17MnToUObPn8+8efOYPn16+ZjPP/+cfv36MWbMGABuv/12+vXrxz//+U/AvHL17bffMmrUKLp3787DDz/MrbfeyhdffOHCMxfxDK1D/LmhbzvAfIhtjbx8IHGSuazO2iLSBFgMw7jA7EupSW5uLqGhoeTk5Gg+kjRpWw7ncu3rP+JltfDDH66iXVhA9QNPHYC/9zEbR963Flp1dW2hIiIOcPTfb4+7i01EXCu+bQhD4yKw2Q3m/LSv5oFhMdB1lLmcOtsVpYmIOI0CkojUqqxx5H9WZZB3ocaRZZO109+H4rMuqExExDkUkESkVldeEkmXyBacLizhozUX6AEWNwJCY+DMSdjyP9cVKCLSwBSQRKRWVquFaaVXkWat3EuJzV7DQC9InGwua7K2iHgwBSQRccgtie0Ib+HLwZNnWHyhxpGJE8HiBQd+hqwtritQRKQBKSCJiEP8fbyYcKnZOPKdHy/QODI4GrqbbTb0fDYR8VQKSCLisImXdsTXy0paxilS95+seWCS2eyV9R9CUb5rihMRaUAKSCLisMhgP27q1xaAdy/UOLLTMGjZCQpzYdN8l9QmItKQFJBEpE7KJmt/s+kIB04UVD/Iaj13FUmTtUXEAykgiUiddIsO5vKurbAbMPtCjSMTxoOXLxxeZ75ERDyIApKI1Nn0y82rSB+tOUDu2eLqB7VoBT1uMJfXarK2iHgWBSQRqbMruraia+sg8gpL+Gj1BRpHlnXW3vgJnM11TXEiIg1AAUlE6sxisTD98k5ALY0jOw6BVt2gOB82fuzCCkVELo4CkojUy40J7WgV5MvhnLN8symz+kEWy7nJ2mveBcNwXYEiIhdBAUlE6sXfx4uJl8YCZuNIo6bw0/d28PaH7M1wcI3rChQRuQgKSCJSbxMu7YCvt5X1B3NqbhwZ0BJ63mIua7K2iHgIBSQRqbeIID9uTWwHwDs/XqBxZNlk7c0LoOCECyoTEbk4CkgiclHuGmpO1l60JZP9x2t4rEj7JIjqDSVnzcePiIg0cgpIInJRukYFM6xbJIYBs1buq36QxQJJU8zl1FmarC0ijZ4CkohctOmljx/5eO0Bcs7U0Diy923g0wKO7YD9K11YnYhI3SkgichFGxoXQffoYAqKbHy4OqP6Qf4h0OeX5rKezyYijZwCkohcNIvFwrTLzLlIs3/aR3FNjSPLJmtv+RzyjrqoOhGRulNAEpEGcUNCW1oF+XEk5yxfbzxS/aA2faFtItiLIf191xYoIlIHCkgi0iD8vL2YPLgjAP+6UOPIsqtIqbPAXsOVJhERN1NAEpEGM/7Sjvj7WNl0KJfVe2vod9TrFvALhZP7YO8yV5YnIuIwBSQRaTDhLXy5NbE9AO+sqKFxpG8L6DvOXNZkbRFppBSQRKRB3VU6WfvbrVnsPVZD48j+pQ+w3fY15NYwX0lExI0UkESkQXWJDGJ499aljSNruIoUFQ8dBoNhg3XzXFugiIgDFJBEpMFNu9y8ivTftQc5VVBU/aCyq0ips8Fuc01hIiIOUkASkQY3uHME8W1COFNs44OaGkfG3wgBLSH3IOxc4toCRURqoYAkIg3OYrEwvfQq0pyf9lFUUs3t/D7+kDDeXNZkbRFpZBSQRMQpruvTltbBfmTlFvLlhsPVDyr7mm3nYjhVw5UmERE3UEASEafw9bYyeUgsAO/8uLf6xpGt4qDTFYABae+5tD4RkQtRQBIRpxk/qAMBPl5sOZJLyp7j1Q8q66yd9h7Yil1XnIjIBSggiYjThAX68ssks3Hkv3+s4Zb/bmOgRSTkZcH2b1xYnYhIzRSQRMSppg7thMUCS7dls/to3vkDvH2h30RzWZO1RaSRUEASEafq1KoFI3pEAfBuTY8f6T8ZsMCe7+H4btcVJyJSAwUkEXG66aWPH5mfdpAT+dU0jmwZC3HDzeW0Oa4rTESkBgpIIuJ0AzuF07tdKGeL7Xywan/1g8oma6+bByWFritORKQaCkgi4nSVGkem7KewpJpHi3QdDcFtoeA4bP3CxRWKiFSmgCQiLnFt7zZEh/hz9HQhX6w/cv4AL29InGQur53l2uJERKpQQBIRl/DxsjJlaCwA7/y4p/rGkYmTwGKF/Svg6HbXFigiUoECkoi4zB0DOhDo68W2zNOs3FVN48jQdnDJNeayriKJiBspIImIy4QG+nBbUgwA76zYU/2gpNLns63/AIrPuKgyEZHKFJBExKXuKm0cuWz7UXZmnT5/QJdfQFgHOJsDmz91fYEiIiggiYiLdYgIZHR8NADvrqymcaTVC/pPMZfVWVtE3EQBSURcruyW//lphzieV03Po34TweoNB9dA5kYXVyciooAkIm7Qv2NL+saEUVRiZ97PGecPCGoN3a8zlzVZW0TcQAFJRFzOYrGUP35k7s/7OFtcTePIss7aGz6Gwmoecisi4kQKSCLiFtf0iqZdWADH8or4PP3w+QM6XQERcVB0GjZ94voCRaRZU0ASEbfw9rIyZUgsYN7yf17jSIvl3GTtNf+G6hpLiog4iQKSiLjNuIExBPl5syMrjx92Hjt/QN87wcsPMjfA4TTXFygizZYCkoi4TYi/D+MGlDaO/LGaxpEtIqDnTeayJmuLiAspIImIW00ZEovVAj/uPMb2zGoaR/Yv7ay9aT6cOeXS2kSk+VJAEhG3igkP5JpebQD4d3WPH+lwKUT2gOIC8442EREXUEASEbebVto48rN1hzl6ukrjSIvl3C3/a9/VZG0RcQkFJBFxu8QOLUnsEEaRzc7cn/efP6DPbeAdAEe3woFVri9QRJodBSQRaRSmX94ZgHk/7z+/cWRAGPS+1VzW89lExAUUkESkURgVH0X7lgGcyC/i03WHzh9Q9jXb5s+g4IRLaxOR5kcBSUQaBW8vK1OHmnOR/r1iL3Z7lblGbRMhug/YCiH9AzdUKCLNiQKSiDQatyW1J9jPm13ZeSzfebTyRk3WFhEXUkASkUYj2N+H2wdeoHFk77HgGwwndsPeH1xcnYg0JwpIItKoTBnaCS+rhZW7jrPlcG7ljX7B0OeX5nKqOmuLiPMoIIlIo9IuLIBre5c1jtx7/oCyr9m2fgF52S6sTESaEwUkEWl0pl1mTtb+fP0hsnPPVt4Y3RvaDwB7Cayb64bqRKQ5UEASkUYnISaMAbEtKbYZvJdSTePIsuezpc4Gu92ltYlI86CAJCKN0rTLShtHrtrPmaIqjSN73gz+oXAqA3Z/54bqRKSpU0ASkUZpZHwUHcIDOVVQzPy0g5U3+gZC3zvNZXXWFhEnUEASkUbJy2rhrqGxALxbXePIpNKv2XYshJxqOm+LiFwEBSQRabR+mRRDsL83e47l8/32KnesRXaDjkPBsGmytog0OLcHpJkzZxIbG4u/vz+DBg1i9erVNY5dsGABSUlJhIWF0aJFCxISEpg7d+55Y0aNGkVERAQWi4X09PTzjnP27FnuvfdeIiIiCAoK4tZbbyUrK6uhT01ELlILP2/uHNQBgH9V1ziy7Jb/1DlgK3FhZSLS1Lk1IH300UfMmDGDJ598krS0NPr27cvo0aPJzq6+t0l4eDiPP/44KSkpbNiwgalTpzJ16lQWLVpUPiY/P5/LLruMF154ocb3feihh/jiiy/473//y/Llyzl8+DC33HJLg5+fiFy8KUNi8bZa+HnPCTYdyqm8scf1EBgBpw/DzsXuKVBEmiSLYbjvgUaDBg1iwIABvPnmmwDY7XZiYmK4//77efTRRx06RmJiImPGjOGZZ56ptH7fvn106tSJdevWkZCQUL4+JyeHyMhIPvjgA8aOHQvAtm3b6NGjBykpKVx66aXVvk9hYSGFhYXlP+fm5hITE0NOTg4hISF1OW0RqaMHP1zHZ+mHublfO14dl1B54+I/w0+vQ9xImPCJW+oTEc+Rm5tLaGhorf9+u+0KUlFREampqYwYMeJcMVYrI0aMICUlpdb9DcNg6dKlbN++nSuuuMLh901NTaW4uLjS+3bv3p0OHTpc8H2Tk5MJDQ0tf8XExDj8niJyccpu+f9i/WEyc6o0juw/xfxz17dwspqeSSIi9eC2gHTs2DFsNhtRUVGV1kdFRZGZmVnjfjk5OQQFBeHr68uYMWN44403GDlypMPvm5mZia+vL2FhYXV638cee4ycnJzy14EDBxx+TxG5OL3bhzKoUzgldoM5Kfsqb4zoAp2vAgxIm+OO8kSkCXL7JO26Cg4OJj09nTVr1vDss88yY8YMli1b5vT39fPzIyQkpNJLRFxn+uXmVaT3f95PfmGVCdllt/ynzYWSIhdXJiJNkdsCUqtWrfDy8jrv7rGsrCyio6Nr3M9qtRIXF0dCQgIPP/wwY8eOJTk52eH3jY6OpqioiFOnTtXpfUXEvYZ3b01sRCC5Z0vObxzZ7VoIioL8bNj+lXsKFJEmxW0BydfXl/79+7N06dLydXa7naVLlzJ48GCHj2O32ytNnq5N//798fHxqfS+27dvJyMjo07vKyKuZbVayh9i++6KvdgqNo708oHESeayOmuLSAPwduebz5gxg8mTJ5OUlMTAgQN57bXXyM/PZ+pU83L5pEmTaNeuXfkVouTkZJKSkujSpQuFhYV8/fXXzJ07l7feeqv8mCdOnCAjI4PDhw8DZvgB88pRdHQ0oaGhTJs2jRkzZhAeHk5ISAj3338/gwcPrvEONhFpHG7t356XFu9g3/EClm7NYlTPCld9EyfBDy/B3h/g2C5oFee+QkXE47k1II0bN46jR4/yxBNPkJmZSUJCAgsXLiyfuJ2RkYHVeu4iV35+Pvfccw8HDx4kICCA7t27M2/ePMaNG1c+5vPPPy8PWAC33347AE8++SRPPfUUAK+++ipWq5Vbb72VwsJCRo8ezT/+8Q8XnLGIXIxAX2/GD+rAP5bt5p0VeysHpLAO0HUU7FwEqbNg9LPuK1REPJ5b+yB5Mkf7KIhIw8rKPctlL3xHsc3g8/uG0qd92LmN2xfCf8ZBQEuYsQ18/N1Wp4g0To2+D5KISH1Ehfhzfd+2ALzz497KG7uOhJD2cOYkbP3cDdWJSFOhgCQiHqdssvZXG49w+NSZcxusXtB/srmsydoichEUkETE4/RsG8qQLhHY7AZzftpXeWO/iWDxgowUyN7qlvpExPMpIImIR5p+uXkV6YPVGeRVbBwZ0ga6XWMur53lhspEpClQQBIRjzTsktZ0jmzB6bMl/HdtlUf/JN1l/rn+QyjKd31xIuLxFJBExCNVahy5skrjyM5XQctYKMyBTQvcU6CIeDQFJBHxWLf0a0/LQB8OnDjDki0VHjZttUL/KeZyqr5mE5G6U0ASEY8V4OvFhEs7AtXc8p8wAaw+cCgVDqe7vjgR8WgKSCLi0SYO7oivl5W1+0+yLuPkuQ1BkRB/g7msq0giUkcKSCLi0VoH+3NjQmnjyBVVriL1L33s0MZPoPC0iysTEU+mgCQiHm9a6S3/32w8woETBec2xF4GEV2hKA82fOym6kTEEykgiYjH6x4dwuVdW2E3qNw40mI5d8v/2lmgR0+KiIMUkESkSSi75f/DNQc4fbb43Ia+t4O3P2RtNCdsi4g4QAFJRJqEKy+JpGvrIPIKS/hoTYXGkYHh0PNmc1nPZxMRBykgiUiTYLGcaxw5a+U+Smz2cxvLvmbbNB/OnKxmbxGRyhSQRKTJuKlfOyJa+HLo1BkWbc46t6H9AIjqBSVnYf1H7itQRDyGApKINBn+PhUaR67Yc26DxXKus/badzVZW0RqpYAkIk3KxMEd8fW2si7jFKn7K3yd1mcc+LSAY9th/0/uK1BEPIICkog0Ka2C/LilXzsA/l3xKpJ/CPQeay5rsraI1EIBSUSanLtKJ2sv3JRZuXFkUmln7a2fQ/4xN1QmIp5CAUlEmpxLooK58pJI7Aa8u7LC40fa9jNftiJIf999BYpIo6eAJCJN0vTSx498vOYAOWcqNI6s2Fnbbq9mTxERBSQRaaIui2tFt6hg8otsfLQm49yGXreCXwic3At7l7uvQBFp1BSQRKRJslgs5Q+xnb1yH8VljSN9W5h3tIEma4tIjRSQRKTJujGhLa2C/Dicc5ZvNmWe21A2WXvbV3A6s/qdRaRZU0ASkSbLz9uLSYNLG0f+uAejrEFkVE+IGQSGDdbNdWOFItJYKSCJSJM2flAH/LytbDiYw9qKjSPLJmunzgG7zT3FiUijpYAkIk1aRJAftyS2B8yrSOXib4SAlpBzAHZ966bqRKSxUkASkSZvWmnjyMVbsth/PN9c6RMAfe80l9fOclNlItJYKSCJSJMX1zqIX3RvjWHAuysqNI4sm6y9cxGcOuCe4kSkUVJAEpFmYXrpVaSP1x4kp6C0cWSrrhB7ORh2SHvPjdWJSGOjgCQizcLgLhH0aBPCmWIbH6yu0Diy7CpS2ntgK65+ZxFpdhSQRKRZsFgs5VeRZv+0l6KS0saR3a+HwFaQlwk7FrqxQhFpTBSQRKTZuL5vW1oH+5GVW8jXG4+YK719IXGiuazO2iJSSgFJRJoNX28rk4fEAvDOigqNIxMnm3/u/g5O7K1+ZxFpVhSQRKRZuXNgB/x9rGw6lMuqvSfMleGdoMtwczl1tttqE5HGQwFJRJqVli18Gdu/rHFkxVv+Sztrr5sHJUVuqExEGhMFJBFpdu4a2gmLBZZuy2LP0Txz5SVXQ3AbKDgG275wb4Ei4nYKSCLS7HSODGJ49yizceTK0qtIXt6QOMlcVmdtkWZPAUlEmqXpl5u3/H+SepCT+aVfqSVOAosV9v0IR3e4sToRcTdvdxcgIuIOgzqF06tdCJsO5fLB6gzuvSoOQtubX7Vt/xr+OxnCOpaOLr3breyut4rrKq2vbl1D7H+BY7rk/euzP+ePdeX7gxl2LV5g9Sr9s+rPXuaYSj9XWF/ttjoe46LXW6s5jwauxWJBzqeAJCLNktk4sjMPfpTO7J/2Mf3yTvh5e8GA6WZAyt5ivkSaumoDWF3CWl0DXx3CXv8p5iOB3EABSUSarWt7t+H5b7aRmXuWL9cf4db+7SFuOIz/BHIPnxtY6b+wLTWvq7S+unV12Z8a1jnjvRpyf84f69C5NnCthmE+Y8+wgd1W+mfVn23mmLKfKy5X3XbBY9R1vb0Bjl2H/WtTXk8jfNROl18oIImIuFpZ48gXFm7jnRV7uSWxHRaLBbqOdHdpIg3HMKoJUzWFrItZ70ggreP6lrFu+2tTQBKRZu3OgR14felOth7JJWX3cYbEtXJ3SSINy2Ix79LUP/l1orvYRKRZCw304bak0saRK/SYERExKSCJSLM3tbRx5HfbstmVnefuckSkEVBAEpFmL7ZVC0bFRwEVGkeKSLOmgCQiAky/vDMA81MPcjyv0M3ViIi7KSCJiABJHVvSt30ohSV23l+V4e5yRMTNFJBERDAbR04rvYr0Xso+zhY70D9GRJos3fMnIlLqml7RtA3153DOWV5dsoPe7UOxYCnvPWihrA+huc782VJpm7necq5vYemY8u2lG8r2p3Sdpep4S8X3O/89K26rtH/V96hw/PJWi7WdQ4XjnTuOpdrtVc/h3HtUOedK9dXxHKoeT4/GEBdQQBIRKeXjZWXK0Fie+3obb/+wx93liAOqBqjydRYL3lYLXtayP614Wy14e1Vcb8XLasHHq/LP58aY+3iV/uxd5WdzX2uF9ygd52U9/73r8L4Vf/ayWvCxWiu9Z3XvodDY8BSQREQqmHBpR7YeOc3hU2eA0sefGmBgmE+vKB1nGAYGnFtX+sDUc+tKx5c9Z7V0Hypsp8L+ZcejynijuvHlz241KtRTucZzz3U1zn+P8uMYFc6vuvMyKtVf29+DO1T9+6+whSI31OMuVgvVBrNzIexcGKsurFUXCn1qColVjllTSHTkfS8YEr0sRLTwxd/Hyy1/pwpIIiIVBPp68+q4BHeX4bEqh8DzA1Sl0HWBoFied84LfucH0coBz1xnN8BuNyixG9jsdkrsBiW2Cj/bDGx2g+IqP5fYDUqq/GyzGxTb7JV+No9XdZ29wnuce69iW+Wfy8ZU/bnsGLYK289/j+qTqN2AohJ7kwuFc+4ayJWXRLrlvRWQRESkwZTPZ6owd0oajmEYDgQ1c119glp5aKyyv7mt6rqq71FzkKxaS3WhsLjs5wrH8LG6738/CkgiIiIewmIp/RrKPd86NSu6zV9ERESkCgUkERERkSoUkERERESqUEASERERqUIBSURERKQKBSQRERGRKhSQRERERKpQQBIRERGpQgFJREREpAoFJBEREZEqFJBEREREqlBAEhEREalCAUlERESkCgUkERERkSq83V2ApzIMA4Dc3Fw3VyIiIiKOKvt3u+zf8ZooINXT6dOnAYiJiXFzJSIiIlJXp0+fJjQ0tMbtFqO2CCXVstvtHD58mODgYCwWS4MdNzc3l5iYGA4cOEBISEiDHbcxaernqPPzfE39HJv6+UHTP0edX/0ZhsHp06dp27YtVmvNM410BamerFYr7du3d9rxQ0JCmuT/6Ctq6ueo8/N8Tf0cm/r5QdM/R51f/VzoylEZTdIWERERqUIBSURERKQKBaRGxs/PjyeffBI/Pz93l+I0Tf0cdX6er6mfY1M/P2j656jzcz5N0hYRERGpQleQRERERKpQQBIRERGpQgFJREREpAoFJBEREZEqFJDcYObMmcTGxuLv78+gQYNYvXr1Bcf/97//pXv37vj7+9O7d2++/vprF1Vaf3U5x9mzZ2OxWCq9/P39XVht3fzwww9cf/31tG3bFovFwmeffVbrPsuWLSMxMRE/Pz/i4uKYPXu20+usr7qe37Jly877/CwWC5mZma4puI6Sk5MZMGAAwcHBtG7dmptuuont27fXup+n/B7W5/w87Xfwrbfeok+fPuVNBAcPHsw333xzwX085fODup+fp31+VT3//PNYLBYefPDBC45z9WeogORiH330ETNmzODJJ58kLS2Nvn37Mnr0aLKzs6sd/9NPP3HHHXcwbdo01q1bx0033cRNN93Epk2bXFy54+p6jmB2Sz1y5Ej5a//+/S6suG7y8/Pp27cvM2fOdGj83r17GTNmDFdddRXp6ek8+OCDTJ8+nUWLFjm50vqp6/mV2b59e6XPsHXr1k6q8OIsX76ce++9l59//pklS5ZQXFzMqFGjyM/Pr3EfT/o9rM/5gWf9DrZv357nn3+e1NRU1q5dyy9+8QtuvPFGNm/eXO14T/r8oO7nB571+VW0Zs0a3n77bfr06XPBcW75DA1xqYEDBxr33ntv+c82m81o27atkZycXO342267zRgzZkyldYMGDTJ+/etfO7XOi1HXc5w1a5YRGhrqouoaFmB8+umnFxzzhz/8wejZs2eldePGjTNGjx7txMoahiPn9/333xuAcfLkSZfU1NCys7MNwFi+fHmNYzzx97CMI+fnyb+DZVq2bGm888471W7z5M+vzIXOz1M/v9OnTxtdu3Y1lixZYlx55ZXGAw88UONYd3yGuoLkQkVFRaSmpjJixIjydVarlREjRpCSklLtPikpKZXGA4wePbrG8e5Wn3MEyMvLo2PHjsTExNT6X0qextM+w/pKSEigTZs2jBw5kpUrV7q7HIfl5OQAEB4eXuMYT/4MHTk/8NzfQZvNxocffkh+fj6DBw+udownf36OnB945ud37733MmbMmPM+m+q44zNUQHKhY8eOYbPZiIqKqrQ+KiqqxvkamZmZdRrvbvU5x27duvHuu+/yv//9j3nz5mG32xkyZAgHDx50RclOV9NnmJuby5kzZ9xUVcNp06YN//znP5k/fz7z588nJiaGYcOGkZaW5u7SamW323nwwQcZOnQovXr1qnGcp/0elnH0/Dzxd3Djxo0EBQXh5+fHb37zGz799FPi4+OrHeuJn19dzs8TP78PP/yQtLQ0kpOTHRrvjs/Q22lHFnHQ4MGDK/2X0ZAhQ+jRowdvv/02zzzzjBsrE0d069aNbt26lf88ZMgQdu/ezauvvsrcuXPdWFnt7r33XjZt2sSKFSvcXYpTOHp+nvg72K1bN9LT08nJyeGTTz5h8uTJLF++vMYQ4Wnqcn6e9vkdOHCABx54gCVLljTqyeQKSC7UqlUrvLy8yMrKqrQ+KyuL6OjoaveJjo6u03h3q885VuXj40O/fv3YtWuXM0p0uZo+w5CQEAICAtxUlXMNHDiw0YeO++67jy+//JIffviB9u3bX3Csp/0eQt3OrypP+B309fUlLi4OgP79+7NmzRr+/ve/8/bbb5831hM/v7qcX1WN/fNLTU0lOzubxMTE8nU2m40ffviBN998k8LCQry8vCrt447PUF+xuZCvry/9+/dn6dKl5evsdjtLly6t8bvlwYMHVxoPsGTJkgt+F+1O9TnHqmw2Gxs3bqRNmzbOKtOlPO0zbAjp6emN9vMzDIP77ruPTz/9lO+++45OnTrVuo8nfYb1Ob+qPPF30G63U1hYWO02T/r8anKh86uqsX9+w4cPZ+PGjaSnp5e/kpKSGD9+POnp6eeFI3DTZ+i06d9SrQ8//NDw8/MzZs+ebWzZssW4++67jbCwMCMzM9MwDMOYOHGi8eijj5aPX7lypeHt7W289NJLxtatW40nn3zS8PHxMTZu3OiuU6hVXc/xL3/5i7Fo0SJj9+7dRmpqqnH77bcb/v7+xubNm911Chd0+vRpY926dca6desMwHjllVeMdevWGfv37zcMwzAeffRRY+LEieXj9+zZYwQGBhq///3vja1btxozZ840vLy8jIULF7rrFC6oruf36quvGp999pmxc+dOY+PGjcYDDzxgWK1W49tvv3XXKVzQ//3f/xmhoaHGsmXLjCNHjpS/CgoKysd48u9hfc7P034HH330UWP58uXG3r17jQ0bNhiPPvqoYbFYjMWLFxuG4dmfn2HU/fw87fOrTtW72BrDZ6iA5AZvvPGG0aFDB8PX19cYOHCg8fPPP5dvu/LKK43JkydXGv/xxx8bl1xyieHr62v07NnT+Oqrr1xccd3V5RwffPDB8rFRUVHGtddea6SlpbmhaseU3dZe9VV2TpMnTzauvPLK8/ZJSEgwfH19jc6dOxuzZs1yed2Oquv5vfDCC0aXLl0Mf39/Izw83Bg2bJjx3Xffuad4B1R3bkClz8STfw/rc36e9jt41113GR07djR8fX2NyMhIY/jw4eXhwTA8+/MzjLqfn6d9ftWpGpAaw2doMQzDcN71KRERERHPozlIIiIiIlUoIImIiIhUoYAkIiIiUoUCkoiIiEgVCkgiIiIiVSggiYiIiFShgCQiIiJShQKSiIiISBUKSCIiDWDZsmVYLBZOnTrl7lJEpAEoIImIiIhUoYAkIiIiUoUCkog0CXa7neTkZDp16kRAQAB9+/blk08+Ac59/fXVV1/Rp08f/P39ufTSS9m0aVOlY8yfP5+ePXvi5+dHbGwsL7/8cqXthYWFPPLII8TExODn50dcXBz//ve/K41JTU0lKSmJwMBAhgwZwvbt25174iLiFApIItIkJCcn89577/HPf/6TzZs389BDDzFhwgSWL19ePub3v/89L7/8MmvWrCEyMpLrr7+e4uJiwAw2t912G7fffjsbN27kqaee4s9//jOzZ88u33/SpEn85z//4fXXX2fr1q28/fbbBAUFVarj8ccf5+WXX2bt2rV4e3tz1113ueT8RaRhWQzDMNxdhIjIxSgsLCQ8PJxvv/2WwYMHl6+fPn06BQUF3H333Vx11VV8+OGHjBs3DoATJ07Qvn17Zs+ezW233cb48eM5evQoixcvLt//D3/4A1999RWbN29mx44ddOvWjSVLljBixIjzali2bBlXXXUV3377LcOHDwfg66+/ZsyYMZw5cwZ/f38n/y2ISEPSFSQR8Xi7du2ioKCAkSNHEhQUVP5677332L17d/m4iuEpPDycbt26sXXrVgC2bt3K0KFDKx136NCh7Ny5E5vNRnp6Ol5eXlx55ZUXrKVPnz7ly23atAEgOzv7os9RRFzL290FiIhcrLy8PAC++uor2rVrV2mbn59fpZBUXwEBAQ6N8/HxKV+2WCyAOT9KRDyLriCJiMeLj4/Hz8+PjIwM4uLiKr1iYmLKx/3888/lyydPnmTHjh306NEDgB49erBy5cpKx125ciWXXHIJXl5e9O7dG7vdXmlOk4g0XbqCJCIeLzg4mN/97nc89NBD2O12LrvsMnJycli5ciUhISF07NgRgKeffpqIiAiioqJ4/PHHadWqFTfddBMADz/8MAMGDOCZZ55h3LhxpKSk8Oabb/KPf/wDgNjYWCZPnsxdd93F66+/Tt++fdm/fz/Z2dncdttt7jp1EXESBSQRaRKeeeYZIiMjSU5OZs+ePYSFhZGYmMgf//jH8q+4nn/+eR544AF27txJQkICX3zxBb6+vgAkJiby8ccf88QTT/DMM8/Qpk0bnn76aaZMmVL+Hm+99RZ//OMfueeeezh+/DgdOnTgj3/8oztOV0ScTHexiUiTV3aH2cmTJwkLC3N3OSLiATQHSURERKQKBSQRERGRKvQVm4iIiEgVuoIkIiIiUoUCkoiIiEgVCkgiIiIiVSggiYiIiFShgCQiIiJShQKSiIiISBUKSCIiIiJVKCCJiIiIVPH/AXGTLT3UfExnAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lr: float = 4e-2\n",
    "n_epoch: int = 3\n",
    "n_splits: int = 3\n",
    "batch_size: int = 512\n",
    "verbose: bool = True\n",
    "\n",
    "dataset = pd.read_csv(\"./revlog_history.tsv\", sep='\\t', index_col=None, dtype={'r_history': str ,'t_history': str} )\n",
    "dataset = dataset[(dataset['i'] > 1) & (dataset['delta_t'] > 0) & (dataset['t_history'].str.count(',0') == 0)]\n",
    "if dataset.empty:\n",
    "    raise ValueError('Training data is inadequate.')\n",
    "dataset['tensor'] = dataset.progress_apply(lambda x: lineToTensor(list(zip([x['t_history']], [x['r_history']]))[0]), axis=1)\n",
    "dataset['group'] = dataset['r_history'] + dataset['t_history']\n",
    "print(\"Tensorized!\")\n",
    "\n",
    "n_pre_train_groups = len(dataset[dataset['i'] == 2]['group'].unique())\n",
    "if n_pre_train_groups < n_splits:\n",
    "    print(\"Not enough groups for pre-training. Splitting into {} folds.\".format(n_pre_train_groups))\n",
    "    n_splits = n_pre_train_groups\n",
    "\n",
    "w = []\n",
    "plots = []\n",
    "if n_splits > 1:\n",
    "    sgkf = StratifiedGroupKFold(n_splits=n_splits)\n",
    "    for train_index, test_index in sgkf.split(dataset, dataset['i'], dataset['group']):\n",
    "        print(\"TRAIN:\", len(train_index), \"TEST:\",  len(test_index))\n",
    "        train_set = dataset.iloc[train_index].copy()\n",
    "        test_set = dataset.iloc[test_index].copy()\n",
    "        trainer = Trainer(train_set, test_set, init_w, n_epoch=n_epoch, lr=lr, batch_size=batch_size)\n",
    "        w.append(trainer.train(verbose=verbose))\n",
    "        plots.append(trainer.plot())\n",
    "else:\n",
    "    trainer = Trainer(dataset, dataset, init_w, n_epoch=n_epoch, lr=lr, batch_size=batch_size)\n",
    "    w.append(trainer.train(verbose=verbose))\n",
    "    plots.append(trainer.plot())\n",
    "\n",
    "w = np.array(w)\n",
    "avg_w = np.round(np.mean(w, axis=0), 4)\n",
    "w = avg_w.tolist()\n",
    "print(\"\\nTraining finished!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1.5175, 2.0482, 4.963, -1.7817, -1.2271, 0.05, 1.4452, -0.1685, 0.8918, 2.0282, -0.2125, 0.3441, 0.5237, 0.01, 2.1869]\n",
      "1:again, 2:hard, 3:good, 4:easy\n",
      "\n",
      "first rating: 1\n",
      "rating history: 1,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,2d,3d,6d,11d,20d,1.2m,2.1m,3.6m,5.9m,9.6m\n",
      "difficulty history: 0,8.5,8.3,8.2,8.0,7.9,7.7,7.6,7.5,7.3,7.2\n",
      "\n",
      "first rating: 2\n",
      "rating history: 2,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,4d,9d,20d,1.4m,2.7m,5.1m,9.2m,1.3y,2.2y,3.6y\n",
      "difficulty history: 0,6.7,6.7,6.6,6.5,6.4,6.3,6.3,6.2,6.1,6.1\n",
      "\n",
      "first rating: 3\n",
      "rating history: 3,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,6d,16d,1.3m,3.0m,6.4m,1.0y,2.0y,3.5y,6.0y,10.0y\n",
      "difficulty history: 0,5.0,5.0,5.0,5.0,5.0,5.0,5.0,5.0,5.0,5.0\n",
      "\n",
      "first rating: 4\n",
      "rating history: 4,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,8d,25d,2.3m,5.7m,1.0y,2.2y,4.2y,7.8y,13.6y,22.7y\n",
      "difficulty history: 0,3.2,3.3,3.4,3.4,3.5,3.6,3.7,3.7,3.8,3.8\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(w)\n",
    "\n",
    "class Collection:\n",
    "    def __init__(self, w: List[float]) -> None:\n",
    "        self.model = FSRS(w)\n",
    "        self.model.eval()\n",
    "\n",
    "    def predict(self, t_history: str, r_history: str):\n",
    "        with torch.no_grad():\n",
    "            line_tensor = lineToTensor(list(zip([t_history], [r_history]))[0]).unsqueeze(1)\n",
    "            output_t = self.model(line_tensor)\n",
    "            return output_t[-1][0]\n",
    "\n",
    "    def batch_predict(self, dataset):\n",
    "        fast_dataset = RevlogDataset(dataset)\n",
    "        with torch.no_grad():\n",
    "            outputs, _ = self.model(fast_dataset.x_train.transpose(0, 1))\n",
    "            stabilities, difficulties = outputs[fast_dataset.seq_len-1, torch.arange(len(fast_dataset))].transpose(0, 1)\n",
    "            return stabilities.tolist(), difficulties.tolist()\n",
    "        \n",
    "requestRetention = 0.9\n",
    "\n",
    "my_collection = Collection(w)\n",
    "preview_text = \"1:again, 2:hard, 3:good, 4:easy\\n\"\n",
    "for first_rating in (1,2,3,4):\n",
    "    preview_text += f'\\nfirst rating: {first_rating}\\n'\n",
    "    t_history = \"0\"\n",
    "    d_history = \"0\"\n",
    "    r_history = f\"{first_rating}\"  # the first rating of the new card\n",
    "    # print(\"stability, difficulty, lapses\")\n",
    "    for i in range(10):\n",
    "        states = my_collection.predict(t_history, r_history)\n",
    "        # print('{0:9.2f} {1:11.2f} {2:7.0f}'.format(\n",
    "            # *list(map(lambda x: round(float(x), 4), states))))\n",
    "        next_t = max(round(float(np.log(requestRetention)/np.log(0.9) * states[0])), 1)\n",
    "        difficulty = round(float(states[1]), 1)\n",
    "        t_history += f',{int(next_t)}'\n",
    "        d_history += f',{difficulty}'\n",
    "        r_history += f\",3\"\n",
    "    preview_text += f\"rating history: {r_history}\\n\"\n",
    "    preview_text += \"interval history: \" + \",\".join([f\"{ivl}d\" if ivl < 30 else f\"{ivl / 30:.1f}m\" if ivl < 365 else f\"{ivl / 365:.1f}y\" for ivl in map(int, t_history.split(','))]) + \"\\n\"\n",
    "    preview_text += f\"difficulty history: {d_history}\\n\"\n",
    "print(preview_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([5.6139, 4.9630])\n",
      "tensor([16.3260,  4.9630])\n",
      "tensor([40.2077,  4.9630])\n",
      "tensor([91.4931,  4.9630])\n",
      "tensor([193.0732,   4.9630])\n",
      "tensor([8.5699, 7.2945])\n",
      "tensor([2.7804, 9.5094])\n",
      "tensor([4.4960, 9.2821])\n",
      "tensor([6.8746, 9.0661])\n",
      "tensor([11.1560,  8.8610])\n",
      "tensor([17.9238,  8.6661])\n",
      "tensor([28.9573,  8.4809])\n",
      "rating history: 3,3,3,3,3,1,1,3,3,3,3,3\n",
      "interval history: 0,6,16,40,91,193,9,3,4,7,11,18,29\n",
      "difficulty history: 0,5.0,5.0,5.0,5.0,5.0,7.3,9.5,9.3,9.1,8.9,8.7,8.5\n"
     ]
    }
   ],
   "source": [
    "test_rating_sequence = \"3,3,3,3,3,1,1,3,3,3,3,3\"\n",
    "requestRetention = 0.9  # recommended setting: 0.8 ~ 0.9\n",
    "easyBonus = 1.3\n",
    "hardInterval = 1.2\n",
    "\n",
    "t_history = \"0\"\n",
    "d_history = \"0\"\n",
    "for i in range(len(test_rating_sequence.split(','))):\n",
    "    rating = test_rating_sequence[2*i]\n",
    "    last_t = int(t_history.split(',')[-1])\n",
    "    r_history = test_rating_sequence[:2*i+1]\n",
    "    states = my_collection.predict(t_history, r_history)\n",
    "    print(states)\n",
    "    next_t = max(1,round(float(np.log(requestRetention)/np.log(0.9) * states[0])))\n",
    "    if rating == '4':\n",
    "        next_t = round(next_t * easyBonus)\n",
    "    elif rating == '2':\n",
    "        next_t = round(last_t * hardInterval)\n",
    "    t_history += f',{int(next_t)}'\n",
    "    difficulty = round(float(states[1]), 1)\n",
    "    d_history += f',{difficulty}'\n",
    "preview_text = f\"rating history: {test_rating_sequence}\\n\"\n",
    "preview_text += f\"interval history: {t_history}\\n\"\n",
    "preview_text += f\"difficulty history: {d_history}\"\n",
    "print(preview_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss before: 0.3251, loss after: 0.3062, improvement: 0.0189\n"
     ]
    }
   ],
   "source": [
    "my_collection = Collection(init_w)\n",
    "stabilities, difficulties = my_collection.batch_predict(dataset)\n",
    "dataset['stability'] = stabilities\n",
    "dataset['difficulty'] = difficulties\n",
    "dataset['p'] = np.exp(np.log(0.9) * dataset['delta_t'] / dataset['stability'])\n",
    "dataset['log_loss'] = dataset.apply(lambda row: - np.log(row['p']) if row['y'] == 1 else - np.log(1 - row['p']), axis=1)\n",
    "loss_before = dataset['log_loss'].mean()\n",
    "\n",
    "my_collection = Collection(w)\n",
    "stabilities, difficulties = my_collection.batch_predict(dataset)\n",
    "dataset['stability'] = stabilities\n",
    "dataset['difficulty'] = difficulties\n",
    "dataset['p'] = np.exp(np.log(0.9) * dataset['delta_t'] / dataset['stability'])\n",
    "dataset['log_loss'] = dataset.apply(lambda row: - np.log(row['p']) if row['y'] == 1 else - np.log(1 - row['p']), axis=1)\n",
    "loss_after = dataset['log_loss'].mean()\n",
    "\n",
    "tmp = dataset.copy()\n",
    "tmp['stability'] = tmp['stability'].map(lambda x: round(x, 2))\n",
    "tmp['difficulty'] = tmp['difficulty'].map(lambda x: round(x, 2))\n",
    "tmp['p'] = tmp['p'].map(lambda x: round(x, 2))\n",
    "tmp['log_loss'] = tmp['log_loss'].map(lambda x: round(x, 2))\n",
    "tmp.rename(columns={\"r\": \"grade\", \"p\": \"retrievability\"}, inplace=True)\n",
    "tmp[['id', 'cid', 'review_date', 'r_history', 't_history', 'delta_t', 'grade', 'stability', 'difficulty', 'retrievability', 'log_loss']].to_csv(\"./evaluation.tsv\", sep='\\t', index=False)\n",
    "del tmp\n",
    "print(f\"loss before: {loss_before:.4f}, loss after: {loss_after:.4f}, improvement: {loss_before - loss_after:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R-squared: 0.9336\n",
      "RMSE: 0.0194\n",
      "[0.04347364 0.95252933]\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Last rating: 1\n",
      "R-squared: 0.2674\n",
      "RMSE: 0.0472\n",
      "[0.33667457 0.60661343]\n",
      "\n",
      "Last rating: 2\n",
      "R-squared: 0.5408\n",
      "RMSE: 0.0557\n",
      "[0.05562355 0.88705994]\n",
      "\n",
      "Last rating: 3\n",
      "R-squared: 0.9340\n",
      "RMSE: 0.0202\n",
      "[-0.00462529  1.01432736]\n",
      "\n",
      "Last rating: 4\n",
      "R-squared: 0.4347\n",
      "RMSE: 0.0224\n",
      "[0.28231857 0.71344008]\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABV8AAAPgCAYAAAAlbwyKAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOydd3gU1duG79mWXgglIRBI6L0jRaUJgiCCYi8UAaWpgNgLoCL6CYiogD9FUMQuIAKCgPTepYaWQICQENLL1pnvj81uEtI2yWbTzn1duWB2Z845M7M7+8wz73lfSVEUBYFAIBAIBAKBQCAQCAQCgUAgEDgVVVkPQCAQCAQCgUAgEAgEAoFAIBAIKiPCfBUIBAKBQCAQCAQCgUAgEAgEglJAmK8CgUAgEAgEAoFAIBAIBAKBQFAKCPNVIBAIBAKBQCAQCAQCgUAgEAhKAWG+CgQCgUAgEAgEAoFAIBAIBAJBKSDMV4FAIBAIBAKBQCAQCAQCgUAgKAWE+SoQCAQCgUAgEAgEAoFAIBAIBKWAMF8FAoFAIBAIBAKBQCAQCAQCgaAUEOarQCAQCAQCgUAgEAgEAoFAIBCUAsJ8FQgEAoFAIBAIBAKBQCAQCASCUqBMzdcdO3YwePBggoODkSSJ1atXF7rNtm3b6NChA25ubjRq1Ihly5aV+jgFAoFAIBAIBJUToUcFAoFAIBAIBKVJmZqvaWlptG3bli+//NKh9SMiIhg0aBC9e/fm2LFjTJ48mTFjxrBx48ZSHqlAIBAIBAKBoDIi9KhAIBAIBAKBoDSRFEVRynoQAJIksWrVKoYOHZrvOq+99hrr1q3j5MmT9tcef/xxEhMT2bBhgwtGKRAIBAKBQCCorAg9KhAIBAKBQCBwNpqyHkBR2Lt3L3379s3xWv/+/Zk8eXK+2xgMBgwGg33ZbDZz5swZQkJCUKlEyluBQCAQCAQVD1mWiYmJoX379mg0FUrOVXiKo0dBaFKBQCAQCASVC6FHHadCHZ0bN24QGBiY47XAwECSk5PJyMjAw8Mj1zazZ89m5syZrhqiQCAQCAQCgcs4cOAAnTt3LuthVCmKo0dBaFKBQCAQCASVE6FHC6dCma/F4Y033mDq1Kn25aioKFq1asWOHTsICQlx6VguxqYwYtkRAD5/og3tQ6q5tP/KgslkYseOHfTo0QOtVlvi9p7/4Qinrqfw7J31efbO0JIPUFAotnP4W3Q1Tl5P4b0HmtOnWa1itfXBujNsOBXL8z3CeKZrPSePtGD++u86H284j5tWxZYpd7u077LEke/gL4ei+PzfSwCsndQNf0+dK4coKARnX0cFLuDSNtSb3kYyJKHovLjS8gXuGv52LhNQUH4pT5pUUHLK63U0OcPEwM/3APDT2M6EVPMs4xGVXwo7h4cvJ/DSL/8BsPOVHkiS5OohCgqhvH4PBY4jzmEFIyUG1cbXUF0/DEBUUH+6v/aH0KMOUKHM16CgIGJiYnK8FhMTg6+vb75RBm5ubri5udmX/fz8AAgJCSE0NLTUxpoXCaoENL5XADC6Vyc01LVGUWXBZDJx+vRpQkNDnXKB1vhGoUl1Q+1b0+WfiaqK7RySUg2NrxsNG4QRGlqzWG2F1k9HEyWjKYPzp71sQeObgAUIrlsPnaZqTBt15DuY8V8aGt9kANwDgggN8nXlEAWF4OzrqKAUMRthy0zY+wW4AaEd4JGlWJJVwNtiunoZUBw9CuVLkwpKTnm9jkYnZaDxrQFAUHAIoYE+ZTyi8kth5zA8zR2N73UAateth7tW7eohCgqhvH4PBY4jzmEF4vxm+Ps5SL8FNXxh8GeYfTrBa38IPeoAFeoIdevWjS1btuR4bdOmTXTr1q2MRlQ0MkwW+/8j4tLLcCSC7BjMMgBJGaYyHknVI9VgBsDbrfjPgap5WSMqE9KNThlTUcjep/j85ORqQtY1LjbZUMCaAoEgXxIuw9L7rMYrQJfxMPofCGhQtuOq4lR0PSqo3GQYs+43jBa5DEdS8UnRm+3/12e7jxMIBIIqhcUEm6bDimFW4zWoDTy/A1o/XNYjq1CUqfmamprKsWPHOHbsGAAREREcO3aMK1es0aFvvPEGw4cPt68/btw4Ll26xKuvvsrZs2dZuHAhv/76K1OmTCmL4RcZgylLAEXGpZXhSATZMZitYiopXZhnribNCearv6f1CWl8muvPX2K2PoX5mpOo+Az7/2OS9WU4EoGggnJmLXx1N1w7BO5+8NgKuO8j0LgVvq2gSFQ1PSqo3KRnN1/NwnwtCSn6LG2nN4ljKRAIqiCJUbBsEOyeb13uPBZGb4LqDct0WBWRMk07cOjQIXr37m1ftuXBGjFiBMuWLSM6OtoufAHCwsJYt24dU6ZM4bPPPqNu3bp888039O/f3+VjLw7ZI18jbwnztbxgM8WFeeZ60jJvELzdi38pCsjMJZpY5pGvru+/vKIoClHZI19TROSrQOAwZgNsehf2L7Yu1+kED38L1eqX7bgqMVVNjwoqN9nvN0wWpQxHUvHJHvmaISJfBQJBVSP8b1g9HjISwM0XHvgcWg4t61FVWMrUfO3VqxeKkr8oWLZsWZ7bHD16tBRHVXpknwZ0+VY6iqKIxO3lgOxpB0wmExaLEFeljclkQlJpqOkhAWp0ihm9vnjRkf5uUMdHjYbit1FcVLKJOj7W/F8paeno9VWjqIXJZEKj0aDX6/P8viSkGanmBtXcrMcmPT3d5eemMqFWq9FoNOL3oioQfwl+GwXRx6zL3V+Ae6aDWuRAK02qmh4VlG8URcFsNhdbj+oz9HZtYjIYxO9vARSmZ2STwX4s09Mz0OtFztfyRmHnUOBchCatIpiN3Fj1OkGnlliXg9vDw0shIKxsx1XBqVAFtyo62Z+YZpgsxCQbCPJzL8MRCcCadiDAXcUDDXVcuHChrIdTJVAUheDgIGZUt/5w34yOIq6YP+JeFpkZvWuhlqxTRV3J483dGdbEOgXYx5RARESKS/svKxRFISgoiKioqDzFl9FsPSc2PLSKy89NZcPT05PatWuj0+nKeiiC0uLUKljzIhiSwaMaPPgVNBGRlAJBVcJoNBIdHU16evFrQ3gZLfbfYE/jLSIiEp00uspHYXrmjpoWWmYeS3NSDBFpN109REEhFHYOBc5HaNJKTkIk/P4sQdcOA3A0+AnaP7sANOJ8lxRhvrqQ2xO1R8SlCfO1jFEUBYtF5vWeNahXw5vg4GB0Op348S5lZFkmKTkVrR4kSaJBCSrxmiwyys1UJCA00Mel584Sm4pFtkZO1/Jxtxf/quzIskxqaire3t55VrZMzjBCUlakjbtWTf3qXq4cYqVBURSMRiM3b94kIiKCxo0bi2qilQ2THja+CYcyowtCusLDS8CvbtmOSyAQuBRZlomIiECtVpdIjyZlGFFn/gYH+3vg4y4i5/OjMD2jS0i3F4etW80TrxLUKBCUDoWdQ4HzEJq0CnDmL1g9EQxJJCleTDM9zxsPviyMVychfkFcyO3ma+StNLo1rF5GoxGANRdWDU811Tw1ePjVwMfHF5VKGK+ljSzLpGYYkcygUalwdy/+QwidoiBprPlWtTo3NGrXiABFUVBUBiSVdaqqSqsr0X5UJGRZxmg04u7unrf5agJJI6PTqDCaZZQSnuOqjoeHB1qtlsuXL9uPu6CSEHcBfhsJMSesy3dNhd5vgVrIM4GgqmE0GpFlmZCQEDw9i5/GKM0sIWmsD4a1Ojfc3cVNc34UpmdUWguSxfq69VgKI7u8Udg5FDgXoUkrKWYD/PMOHPgKgFi/NjwYM5rqdRvRoKZ3GQ+u8iDUvQu5PVF7ZJwoulXW6M0WrF6rBJKEWVbQCfPVJdiy65VUJ6kkCZUkISsKFllB46J0XLKioJCVI9Aii6IWNmzVlb10GoxmIyZZETmuS4i4oaiE/PcbrJ0MxlTwrAEPfQWN+pb1qAQCQRlT0ut9djlSQCpjgQNk13YF5YUWCKoSQpNWMm5dhN9HQfRx63L3F5lwvi/XSOXZdnXKdmyVDGG+upAMo82QUJNmtBB5S5ivZY3BJOdYtghh5TJselbtBENOo5IwWhTMsoJbiVtzDPNtZqswX7Owma+eOjUJ6ZnpPWQFjVqYrwIBxnTY8Boc+d66XP8uGPYN+NYu23EJBIJKgZxNy2Z/SCwoOtm1nVzAegKBQFAhObnSWm/AmAIeAfDgYi5Xv4tD/25DJcHgtkKbOhNhvroQvdka+dqsti+HLycQGVf8ZPoC52Aw54xGFgaa67DdGzgjzYNaJYHFtefv9r7EZycLk8V6i+KmVaNWSVhkqzHuqqhkgaDccjPcmmYg9jQgQc9XocerIs2AQCBwGtnNVyFNSkbOYykOpkAgqCSYMjLrDXxrXa7XDYYtAb86/LnlPAB3NqpBLR+RVsKZiJhxF6I3ZpqvQdbiQpG30pCFKipTDObbIl+r+PnYtm0bkiSRmJjo8DYzZsygXbt2Re7LduSLGvnaq1cvJk+enOM1daaBe3s0amkizNe8URQFo8V6LHRqFdrMHLw2Q7YyktdnUiDIxbEf4X+9rMarVy0Yvhp6vymMV4FA4FSUSpJ2wJWaND9ypB3IQ8aI339BeUN8JgWFEncevumbabxKcPfLMGIt+NVBURRWH7sGwBCRcsDpCPPVhdhyvjaq5Y1GJWEwy9xI1heylaA0yZV2oIIYaIsXL8bHxwez2Wx/LTU1Fa1WS69evXKsaxOvFy9eLLTd7t27Ex0djZ+fn1PHm5cQsB1qlVPSDlgvZRZZYdmyZfj7+5e4zcKwGb0Skr1vcFz0RERE8OSTTxIcHIy7uzt169ZlyJAhnD17ttTG7ApMlqz8rlq1hCbTGN+61fo5tP3VrFmTgQMHcuLEiTIecclZuXIl77//flkPQ1BeMabBqvGwejyY0iGsJ4zbBQ16lfXIBAJBJSR7YIcr0g5UBk2aF4qi5Ix8LcaxdJUmzY+qrknzw/Y5FJpUUOX471f4qifEnLTWG3j6D7jnXXsgwMlryVy6mYabRkX/loFlPNjKhzBfXYjNfPV20xASYK1iKopulS0VNe1A7969SU1N5dChQ/bXdu7cSVBQEPv370evzzL1t27dSr169WjYsGGh7ep0OoKCglxSGMlZBbcAey5Ri+y66ErbZ0WnyTR+ixBeYjKZ6NevH0lJSaxcuZLw8HB++eUXWrduXaQIj9LCaDQWf9vMCFetWso0YLOMcYDw8HCio6PZuHEjBoOBQYMGlag/RzCZTKXafkBAAD4+PqXah6CCEnPaGu16/EeQVND7bXhmFfgIQSsQCEoHVxfcqgyaNC9uvyeoILcIRaYya9LCEJpUUGUwpsOfk2DlWDClQejd1kCARvfkWM0W9dq3RSA+7tqyGGmlRpivLkSfab566NSEVrearxGi6FaZkjvtgHVZURTSjGku/3O0kmrTpk2pXbs227Zts7+2bds2hgwZQlhYGPv27cvxeu/evQGQZZnZs2cTFhaGh4cHbdu25ffff8+x7u1TvL7++mtCQkLw9PTkwQcfZN68eXk+xV++fDmhoaH4+fnx+OOPk5KSAsDIkSPZvn07n332mf0Jc2RkJLIC58+eZvijQ/H29iYwMJBnnnmGuLg4e5tpaWkMHz4cb29vateuzdy5c/M8HkVJO5CYmMiYMWOoWbMmvr6+9OnTh+PHj9vfv3jxIkOGDCEwMBBvb286d+7M5s2bc7SxcOFC7mjbks6NgrizTUNefn4EFlnJd19v59SpU1y8eJGFCxfStWtX6tevz5133skHH3xA165d7esdOHCA9u3b4+7uTqdOnVi1ahWSJHHs2DEg74iK1atX57hRcWR/QkNDef/99xk+fDi+vr4899xzAOzatYu7774bDw8PQkJCePHFF0lLy7pmLVq0iMaNG+Pu7k5gYCAPP/ywvdiWLtN0tRvjmZ/tWrVqERQURIcOHZg8eTJRUVE5IisK6zM6OppBgwbh4eFBWFgYP/74I6GhocyfP9++jiRJLFq0iAceeAAvLy9mzZoFwJ9//kmHDh1wd3enQYMGzJw50x6poygKM2bMoF69eri5uREcHMyLL76Y45zfvq82bo8sSUhIYPjw4VSrVg1PT0/uu+8+zp8/b3/fdt42btxI8+bN8fb2ZsCAAURHRyOoJCgKHP4Ovu4NcefApzaM+At6vgIqkfxYIBA4RnH0aKoxlXRTGummNNKMqUKTFqBJ1Wo1V65cAeDkyZPcd999dk06YvhwEuJv2dtMS011SJMWBWdp0rz0idCkD1MYQpMKTVoliD0LX/eBo8ux1ht4HYb/mavQq0VW+Ov4dQCGipQDpYJINOZCMjKnuLtr1ITW8ILwm1y+JYpulSX55XxNN6XjPdvb5eNJfSMVL52XQ+v27t2brVu38vrrrwPWaIJXX30Vi8XC1q1b6dWrFxkZGezfv59nn30WgNmzZ/PDDz+wePFiGjduzI4dO3j66aepWbMmPXv2zNXH7t27GTduHB9//DEPPPAAmzdv5p133sm13sWLF1m9ejVr164lISGBRx99lI8++ohZs2bx2Wefce7cOVq1asV7770HQPXq1Tl16TpjHx/CMyNGsfDzBWRkZPDaa6/x6KOP8u+//wLwyiuvsH37dv78809q1arFm2++yZEjR3Ll87KZr45ELj/yyCN4eHjw999/4+fnx1dffcU999zDuXPnCAgIIDU1lYEDBzJr1izc3Nz4/vvvGTx4MOHh4dSrV49Dhw7x4osv8tniJTRs1R6VMY0t23YgKwqffjo/177WrFkz1xhq1qyJSqXi999/Z/LkyajVuc2Y1NRU7r//fvr168cPP/xAREQEL730UqH7l1c7Be2PjTlz5vDuu+8yffp0wHpOBwwYwAcffMC3337LzZs3mTRpEpMmTWLJkiUcPXqUl156ieXLl9O9e3fi4+PZuXOnPfLVFhFsi3w135bzNSkpiZ9//tm6rk5XaJ9Lly4FYPjw4cTFxbFt2za0Wi1Tp04lNjY2137PmDGDjz76iPnz56PRaNi5cyfDhw9nwYIF3H333Vy8eNEu6KdPn84ff/zBp59+ys8//0zLli25ceOG/QbIds5v39f8GDlyJOfPn2fNmjX4+vry2muvMXDgQE6fPo1Wa32KnJ6ezpw5c1i+fDkqlYqnn36aadOmsWLFiqKcXkF5xJACa6fAid+sy436woNfgVeNQjf989g17m0RhIdOGLQCgaDs9ChUDU0qyzJubm4kJibSp08fxowZw6effkpGRgavvPIqr4wfxTe/rAHgvXfedEiTFgVnadK89Ele+ruqaVJHEZpUaNJKy9EVsH6aNe2VdyA89DU0yH19Bdh78RaxKQb8PbX0bJL7WiFwAkoVIyoqSgGUiIgIl/d977ztSv3X1iq7zt9UvtsTodR/ba0y5ruDLh9HRcdoNCqrV69WjEZjidvaeDJa6f7B38o/uw8rxyJilMtxqYqiKEqqIVVhBi7/SzWkOjz2r7/+WvHy8lJMJpOSnJysaDQaJTY2Vvnxxx+VHj16KIqiKFu2bFEA5fLly4per1c8PT2VPXv25Ghn9OjRyhNPPKEoiqJs3bpVAZSEhARFURTlscceUwYNGpRj/aeeekrx8/OzL0+fPl3x9PRUkpOT7a+98sorSpcuXezLPXv2VF566SX7ssViUSa/+pbSrUcfJTZZb3/d9v0MDw9XUlJSFJ1Op/z666/292/duqV4eHjkaEtRFCUhzaAcj0pQLsSmKEuXLs0xvuzs3LlT8fX1VfR6fY7XGzZsqHz11Vd5bqMoitKyZUvl888/VxRFUf744w/F19dXORVxQzkelaDEJuuV/6ISleNRCYrRbMm1r/nxxRdfKJ6enoqPj4/Su3dv5b333lMuXrxof/+rr75SqlevrmRkZNhfW7RokQIoR48eVRRFyXNfV61apRR2ac++P4qiKPXr11eGDh2aY53Ro0crzz33XI7Xdu7cqahUKiUtLU35/vvvFV9f3xznXVEU5cqtNOV4VIISk2Qdd2Lmuflh5XoFULy8vBQvLy8Fa+YJ5YEHHnCoz4yMDOXMmTMKoBw8mHXdPH/+vAIon376qf01QJk8eXKOdu655x7lww8/zPHa8uXLldq1ayuKoihz585VmjRpkud1xXbOb99XG9nP+blz5xRA2b17t/39uLg4xcPDw/5ZXrp0qQIoFy5csK/z5ZdfKoGBgXm2ryiKkpGRoZw+fTrH56EkOPM6KsjG9eOKsqCDokz3VZQZ1RRl5zxFsVgK3UyWZeWzzeeU+q+tVZ7+Zp9iMhe+TUREhAIoUVFRzhi5oAwoS00qKDnOvo7mdZ0vKz1aVTSpxWJREhISlPfee0+59957c7R99oL1Gvvn9oPK3rNRDmvS7LhKkzqiTwqismrS/LB9toQmFZq00qJPUZSVz1v16HRfRfnuAUVJiSlwk5d/PabUf22t8sbK/4rUldCjjiMiX12ILeeru1ZNaHXrk2SR87VsuT3y1TZt3VPrSeobqS4fj6fW0+F1e/XqRVpaGgcPHiQhIYEmTZrYowVGjRqFXq9n27ZtNGjQgHr16nHq1CnS09Pp169fjnaMRiPt27fPs4/w8HAefPDBHK/dcccdrF27NsdroaGhOfIL1a5dO88nv9k5e/okB/fuJKx29VzvXbx4kYyMDIxGI126dLG/HhAQQNOmTXOt72jk6/Hjx0lNTaV69Zx9ZmRk2Is/pKamMmPGDNatW0d0dDRms5mMjAz7tLR+/fpRv3597u7Ukm497+GBQQPp2PNetG4eRcoZPHHiRIYPH862bdvYt28fv/32Gx9++CFr1qyhX79+nDlzhjZt2uDu7m7fplu3bg63b6Ow/bHRqVOnHMvHjx/nv//+y/HUW1EUZFkmIiKCXr16Ub9+fRo0aMCAAQMYMGAADz74YFbaAY0t7YAt56v19Z07d+Lp6cm+ffv48MMPWbx4scN9njt3Do1GQ4cOHezvN2rUiGrVquXa77z2Z/fu3fbpXgAWiwW9Xk96ejqPPPII8+fPt+/PwIEDGTx4MBqNxn7Ob99XT8/c39czZ86g0WhyfG6rV69O06ZNOXPmjP01T0/PHDnvHPnOCFyHLMtFynXn7+eH6shS2PAmWAzgWwce/hbqdS10W0VR+GRjOAu3Wa9BXRtUt39vBAJB1aY4evR8bIo91VmAl446/o5ry9v7dpSKrkmPHz/O1q1b8fbOHWV89XIEBr3jmtRRnKlJHdEnBVFZNWlhx0FoUitCk5ZfiqpHAfwN11D98aw17ZWkgt5vwl0vF1hoRW+ysOHkDUCkHChNhPnqQuw5X7Vqanq7AXA5Ph1ZVlCpyiaZfFXHZr7ajr4tL6UkSQ5PtSorGjVqRN26ddm6dSsJCQn2KVrBwcGEhISwZ88etm7dSp8+fQCr4AFYt24dderkvKi6ubmVaCy2aSs2JElCLqT4VVpaKj37DuD/Pv4IXw9djvdq167NhQsXHO5f46D5mpqamisvmQ1bnqpp06axadMm5syZQ6NGjfDw8LDmMs1MwO/j48ORI0f4YdV6tv+7mdkfvIfywXv88Ne/WGoWbWqgj48PgwcPZvDgwXzwwQf079+fDz74INfNSH6oVKpcOdluT+Rf2P7Y8PLK+XlPTU3l+eefz5FjykbdunXR6/UcOnSIHTt28M8///Duu+8yY8YMfvhrCx7evvacr1p1zny8YWFh+Pv707RpU2JjY3nsscfYsWNHoX3Wq1ePc+fOOXRc8tufmTNn8tBDD+Va193dnZCQEMLDw9m8eTObNm1iwoQJfPLJJ2zfvt1+zrdt25ZjXw8ePFjsKsZ5fWduP5eCsiMxMZF5a4/i7lV40Qp9UhxT+Z6AK39bX2gyAIYuAs+AQrdVFIX3157h290RALxzfwtG3xVWorELBILKQ3H0qLvGggqrBvPQ6PDSFc98LQoVXZOmpqYyePBgPv74Y/trSRlGohP11AgMJCryUonGlF+fztKkztAnlVGTFnYchCa1IjRp+aUoehQU9BEHmRo/kwCd0VpvYNgSCL2z0C23nIkl1WCmjr8HnernfoAgcA7CfHUhWZGvKoL93dGqJYxmmetJGdStVvrCSJAbmyFuexBUlMjF8kDv3r3Ztm0bCQkJvPLKK/bXe/Towd9//82BAwcYP348AC1atMDNzY0rV67kmUsrL5o2bcrBgwdzvHb7siPodDosFkuO11q0asvG9X8RFhZGNW+PXNs0bNgQrVbL/v377XmgEhISOHfuXK7xqzNPoFlWChQLHTp04MaNG2g0GkJDQ/NcZ/fu3YwcOdIeXZGampqrQIFGo6HrXb3o0K0H/zfrfYIDa3Bgzw7aNHg8z311BEmSaNasGXv27AGgefPmLF++HL1eb480yF60Aqx5ulJSUkhLS7MLO1vhg6LsT1506NCB06dP06hRo1zvybKMXq9Ho9HQt29f+vbty/Tp0/H392f3zu30vW8wWlvka+a5yeusTJw4kdmzZ7Nq1SoefPDBAvsE6+fRbDZz9OhROnbsCMCFCxdISEhwaH/Cw8PzbRvAw8PDfuMxceJEmjVrxokTJ+jQoUOe+/rvv//mEs7NmzfHbDazf/9+unfvDsCtW7cIDw+nRYsWhY5TUH5w9/LBy9e/4JVSouHCWrCsBy8t9J0J3SaCA9W5ZVnhnT9PsmK/NeLn/aGteKZrfSeMXCAQVGWyS1lXqtqKrEk7dOjAypUrCQ0NRaOx3h7HpRrQJmYAEFI/zGFN6ijO1KT56ZOqrknz0mn5ITSpoLzikB61GCB8I1w/CloDNOrncL0BgNXHrgEwpF2wCAosRYT56kLska86NRq1ipAATy7dTCMyLl2Yr2WELfJVLTlesKk80bt3byZOnIjJZMoh/nr27MmkSZMwGo32qrI+Pj5MmzaNKVOmIMsyd911F0lJSezevRtfX19GjBiRq/0XXniBHj16MG/ePAYPHsy///7L33//naNyqSOEhoayf/9+IiMj8fb2xt/fn8dHjOHXH7/n2RHP8ObrrxEQEMCFCxf4+eef+eabb/D29mb06NG88sorVK9enVq1avHWW2+hymPKhC3tgKIoKIp16s7tgs/NzY2+ffvSrVs3hg4dyv/93//RpEkTrl+/zrp163jwwQfp1KkTjRs3ZuXKlQwePBhJknjnnXdyREysXbuWS5cuEdysPd6+fmw/tBNZlglt0AizrOTa14CAgFxjPnbsGNOnT+eZZ56hRYsW6HQ6tm/fzrfffstrr70GwJNPPslbb73F2LFjeeONN4iMjGTOnDk52unSpQuenp68+eabvPjii+zfv59ly5blWKew/cmP1157ja5duzJp0iTGjBmDl5cXp0+fZtOmTSxYsIANGzYQExNDz549qVatGuvXr7cfB5Uk2aORVSrJfn5ux9PTk7FjxzJ9+nSGDh1aYJ9ffPEFzZo1o2/fvjz33HMsWrQIrVbLyy+/jIeHR6GfyXfffZf777+fevXq8fDDD6NSqTh+/DgnT57kgw8+YNmyZVgsFvsx/eGHH/Dw8KB+/fr2c96jR48c+5rXdMPGjRszZMgQxo4dy1dffYWPjw+vv/46derUYciQIYUed0FFQYGrh+Hiv6DPgIA6MHI51O1U+KZYf2te++M/fj98FUmCj4e14dFOIaU8ZoFAUBVQsmlZV0avVURN6unpiUajYcKECXzzzTc88cQTvPrqqwQEBHDo+Gl+/Pln3p/7OZ5e3jzy5HCHNOntuEKT5qdPqromLUpaCKFJBRWW1Btw6k/ISLA+/O/5Ggx4o8A0A9lJTDeyLdyaZmJoe5FyoDQRScVchNkiY7JYBZCH1lpFMsyW9/WWyPtaVhjMtsjXLPO1Ik2z6N27NxkZGTRq1IjAwED76z179iQlJYWmTZtSu3Zt++vvv/8+77zzDrNnz6Z58+YMGDCAdevWERaW9zTXO++8k8WLFzNv3jzatm3Lhg0bmDJlSo6cT44wbdo01Go1LVq0oGbNmly5coWaQbX5btUGZIuFe++9l9atWzN58mT8/f3twvCTTz7h7rvvZvDgwfTt25e77rrL/nQ5OyoJu9CRFYXU1FTat2+f488m9NavX0+PHj0YNWoUTZo04fHHH+fy5cv24zdv3jyqVatG9+7dGTx4MP3798+Rz8nf35+VK1cy+tEHeLB3V77++n98/r9lNGraHIus5Lmvt1O3bl1CQ0OZOXMmXbp0oUOHDnz22WfMnDmTt956CwBvb2/++usvTpw4Qfv27XnrrbdyTIcDa76xH374gfXr19O6dWt++uknZsyYkWOdwvYnP9q0acP27ds5d+4cd999N+3bt+fdd98lODgYAD8/P1atWkWfPn1o3rw5ixcv5tvvltOoaXN0GlUO4aktIH/lpEmTOHPmDL/99luhfQJ8//33BAYG0qNHDx588EHGjh2Lj49PoZ/J/v37s3btWv755x86d+5M165d+fTTT6lf3xpp6O/vz9dff82dd95JmzZt2Lx5M3/99RfVq1e3n/Ps+/rTTz/RsmXLPPtaunQpHTt25P7776dbt24oisL69etzTesSVFDMGXByFVzYDIoMAQ1h1DqHjVeTRWbKL8f4/fBV1CqJ+Y+1E8arQCBwCoqi5Ix8daGkrYiaNDAwkKtXrxIcHMzu3buxZNOkb7/xCr6+fugyI2Ffmf6+Q5r0dlyhSfPTJ1VZkxak0/JDaFJBxUKBa0fgyHKr8ermC60ehq7jHTZeAdafuIHJotC8ti9NAh1JbyAoLpJSkZwmJ3D16lVCQkKIiIjId4pHaZBqMNNq+kYAzr4/AHetmvfXnmbJrgjG3BXG2/eL0H9HMZlMrF+/noEDB5b4h+PTTef4/cAlPhlQG6/qtZE0OlrU9hXFTgpg7NixnD17lp07dxa7DVmWOXU9GQVoFuSDTqMu8bjORCdjssg0quWNp650g/pNFpkz0clIQKs6flxP1HMrzUAtX3eCfIt2E1AUIiMjCQsL4+jRo7Rr167U+ikMWZZJTk7G19c3RwTFrVQD1xIz8HXXElojK7/VpZuppBrMhFTzpJqXLq8mi43tmr5582buuecep7ZdntDr9URERBAWFlbkG828cOZ1tDISHx/Pwq0Xck/zSr4Op/8EfZK1iEHDPqT5NmRC78YEBBSe49VolnnhpyNsPBWDVi3x+RPtGdCqdqHb5YXtehAVFUXdunWL1YagbCkrTSpwDs6+jjrjOi8rCievJdmXvd00NChiPvqKREk1aX56BuBqQjrxaUa83DSkGcy4a9XCmMhGedekZYHQpMVDaNL8yVePmvUQ/jfcDLcuV28EzQaRlmFgQu9GDmlSG49+tZcDEfG8cV8znu/ZsPANbkPoUccRaQdcRIbRGmEpSeCWmQvRZk6IyNeyw15wS5LskXoWRRFfjGzMmTOHfv364eXlxd9//813333HwoULS9yu7amPqojTxfJDrZIwWVyTOsJWPEqtskZ42qbVyxUsbYWzMVqs3yedJqf4tUW+mhyYWlYY//77L6mpqbRu3Zro6GheffVVQkND6dGjR4nbFgjyR4Gog3BpmzXa1cMfWgyxFjNITnSoBb3JwoQVR/j3bCw6jYrFT3egT7PAwjcUCAQCB7ldh1Q2VVJamjQvbJJFq8qaWSUQZEdoUkGZkBJtDQTISMwMBOidOftKggxDkZq6lpjBgYh4JAkeaBdc+AaCEiE8Jhdhy/fqrlHbTb7Q6tY8rxFxwnwtK2xpBySseV8tVLy8r6XNgQMH+L//+z9SUlJo0KABCxYsYMyYMSVq05JNwDorqbcmW+qI0sZisZmvUo5/zVX8s2PMfJhxe5oBjTrz+FhKfnxMJhNvvvkmly5dwsfHh+7du7NixQrxpFxQepgy4Ow6uHXBulyzGTQdABrHoz3SjWae+/4wuy7E4a5V8c3wztzV2LEiCAKBQOAot8uQyuYXloYmzQ+bVrXNhqviEk+QB0KTClxLtnoDigzuftZAAN/im6Zrjl0HoEtYALX9chfAFjgXYb66iIxsxbZshGbmfI2Kz8AiK/kWpRGUHlmRr1YTUJivufn111+d3qYtmkCSJKdGvoJrDFBL5g5objNfS/uzExoaWq5zEhca+WopeeRr//796d+/f4nbEQgcIukqnF4DhmRQqaFRXwhuh/WRnWPcSNLz/A+HOR6ViJdOzbcjO9OlQfVc6yUbkvnmyDd0Cu5Ej/oiakYgEBSd26Mzy7NmKA6loUnzw6bpbA+QK9uxLCnlXZO6AqFJBS7DnAFn/4a4c9blGk2g2cAiBQLkxZ/HrgEwtJ0otOUKhPnqImyRr7ZiWwDB/h7o1CqMFpnriRmEBHiW1fCqLAZTpvkKqFVgkoX56gpsNwdqJz5vcGXka1baAdear+UdU+bDDN3tka+Zx8fkhMhXgcAlyDJcPQg3j1hDxzyqQcuh4F20NAEHI+MZ/8MR4lIN+Hlo+XZkZzrWr5ZjnaikKBbsX8D/jvyPZEMy/Rr0459n/nHizggEgqrC7WaY+NUtPjatqlGJyFeBQFCGpNyA01ut9QZUamjYB+p0oCiBAHlx9kYyZ2+koFOruK913vUHFEXJUURZUDKE+eoibDlf3bRZpoRaJVGvuicXYlOJvJUmzNcywJ52QJJQS8JAcxW2nGTOinoFa/5VcFXkqzBfb8ciy/Zjn1/kq9kJOV8FglInLQ5+HwWXfcHDDQJbQJP+oHZzuAlFUfhh32Vm/nUas6zQLMiHr57pSP3qWYXojt04xty9c/n55M+YZTMAzWo049GWjwqxKxAIikVlTzvgSmyaTpst8lVcmwUCgcuQZTjwPzhxCty1OesNOIHVR60pB3o3q4mfR+5UGb+d+o0Pdn7A1hFbCfBwvICXIH+E+eoiMvKIfAVr6oELsalExqVxd+OaZTG0Ko097QAI89WF2PJoOSvfK2QzQF0QXWm+bSqa+OyA0WyLEJFypVCxHSeTRdy4CMo5kbvgjzEQex1UQ6HpfVC7DUWJLtCbLLyz+iS/Hb4KwKA2tfnk4TZ46jQoisLGixuZs2cOWyK22LfpFdqLad2mcV/j+1BJZVutWSAQVFwqe9oBV2ILFLBFvoLV3HbmrC2BQCDIk/R4WDUO/tsAymCo1Qya3AcaxwMBCkKWFdbkk3IgJjWGiesn8seZPwCYs2cOH97zoVP6reoI89VF5JV2ALIX3Up3+ZgEt+V8VUtgrtoGmquwHWK1E004jT3na+lHV+Yb+VqFoyJs+V61mtzGkTbzxkVRFCyyYjdjBYJyg2yBnXNh22xrEYOAhhD8BAQ1LFIz0UkZjPvhCMejElFJ8OqAZjzfowFGi5Flx35g7t65nIw9CYBaUvNoy0d5udvLdAzuWBp7JRAIqhg281UlSciKItIOFBNFUbIV3JJyvF7Sqb4CgUBQIJf3wh+jIfkaqHTWNANN7sKZ154DkfFcT9Lj466hd7NagPX69vPJn3nh7xe4lXELjUrDm3e9yVs93nJav1UdYb66CH1mbtHsBbcAQmtYpyBG3kpz+ZgEWaa4hC3tgCLMVxdgO8YqJwZ4uXLqf37mq6IoVTYqwphPvlewRjirVRIWWcEsK2jUuVYRCMqOlBhYORYitluX2z4J3d6E3dFFauZARDwTVhwmLtWIn4eWz59oT6sQNR/t+ogFBxZwI/UGAN46b8Z2GMtLXV6ivn99Z++NQCCowtgfbqsk5MzZJoKikz2CWK2SkCTJrvEEAoGgqMiyTGJiYmErwf5FsGMuIOMf3AjuXQCndTj7oY+t0NZ9rYJw16qJTolm/Lrx/Bn+JwBtA9uybOgy2gW1c2q/VR1hvroIW9oBt9tchzCb+RonzNeyIEfka6b56oqcoVWd7JEZzqIsCm7Z+lRJ2IW5RVZyTbuvCpgyI19vz/dqQ6tSYZEtmCwy7lrhvgrKCZe2wR9jIS0WtJ4waC60exLi44vQiMLPB68wb/t1e37Xt4fU4tez73Pf70tIN1lnttTxqcNLXV5ibMex+Lv7l8beCASCKo6c7eGwySKKRBWXTEmDJEmoJAmVBBYld1oHgUAgcITExETmrT2Ku5dP3iuY0uH8Rki4AgxC712fqY8+D24+cPqCU8diMFtY9581wGBIu2C+P/49kzdMJkGfgFal5e0eb/PGXW+gVefOAysoGSKxmIuwFdzKL/I1KiEds0UUo3E1hkxTHMAWsGcRwsopSJLE6tWr83zPmWkHli1bhr+/P+rMcNMFn3xIu3bt7O+PHDmSoUOHlrif7GRFvlo/NDkKtikKoaGhzJ8/36l9lncKinyFrGl7Zhfk5BUICkW2wNYP4fuhVuO1VgsYu9VqvBYBsyyzLfwms9efxSwrdGuswytoMT2Xt+TzA5+TbkqnbWBbvh/6PZdeusQrd74ijFeBQFBqZI98BUTagUwK0qR5YbsXsGk7W7BAYZHENk1qY8aMGaWuSQujKmpSgaA84u7lg5evf+4/ORmv8JV46WPw8vLCq92DuLcdYjVeS4Ft4TdJ1pup4a1l1v5RjFg9ggR9Ah1rd+Twc4d5t+e7wngtJYT56iKyCm7lPOS1fd1x06gwWRSuJ+rLYmhVGqM98lWqsBXr9+7di1qtZtCgQUXetqwEme0Yx92M4YUXXqBBgwa4ubkREhLC4MGD2bJlSyEt5MZ2/oY/P4lNmzY7dby3Y8nMK/vTD9/bRXb2z8/Bgwd57rnnSnUM5Q1jYZGvmaasyQU5eQWCAkmOhu8egO0fAwp0GA5jtliLGRSBFL2J3w9dJTwmFUlS8Kv5Lz9H3cvK8J+QFZn+Dfuz6ZlNHH3+KM+0fQadWlc6+yMQCASZyLeZhori2tQDFVGT2rhx44Zdk/p7e3LvHS2ZOPIxtmzZgi1WoKi3CNOmTSuWpi0Otxu/NqqiJhUIKgSKDJG74fhPYEwFz+rQcUSRC70WldVHrSkHrppW8/eFdejUOj7s8yH7xuyjdWDrUutXINIOuAxDPgW3VCqJ+tU9OReTSsStNOplFuASuAZ72gGynmpXNPN1yZIlvPDCCyxZsoTr168THBxc1kMqFFlRuBZ1hWeHDSCgWjU++eQTWrdujclkYuPGjUycOJGzZ88WqU21JCEh4enljX813xKNz2g0otPlbZTYUguANd2Avf9s5mvNmjVL1H9FQ1EUEfkqqBhc2Awrn4f0ONB5w/3zoc0jRW7mWkI6605Ek2GSASOx2k+ISj2JVq3lqTZPMbXrVCFgBQKBy7Gbr9kEiitLRFVETQoQGRnJ3Xffjb+/P5988glhjZsReTOZg7u2MXHiRNZsPwgUHvl6O97e3nh7e5dobAVpUkeoappUIKgQGFPhzF+QcNm6HNQaGvcDJz+ov5li4NT1JE5dT+b09WSORd3iWqIRgHg2ckedO1g6ZCktarZwar+CvBGRry7CFvmaV67D+tVF3teywmDOLLgl5TTPFEUh3Wh2+V9RRV1qaiq//PIL48ePZ9CgQSxbtizXOn/99RedO3fG3d2dGjVq8OCDDwLQq1cvLl++zJQpU5AkazEByD1FCmD+/PmEhobalw8ePEi/fv2oUaMGfn5+9OzZkyNHjjg8bllW+PCtl5EkiQMHDjBs2DCaNGlCy5YtmTp1Kvv27bOvO2/ePFq3bo2XlxchISFMmDCB1NTUXG3aopcXzfuIjh075Hp/5syZ1KxZE19fX8aNG4fRaLS/16tXLyZNmsTkyZOpUaMG/fv3z7fvpOQUFODg3l2MGT2apKQkJEmicaAPi+Z9hEXOnXbgypUrDBkyBG9vb3x9fXn00UeJiYmxv2875suXLyc0NBQ/Pz8ef/xxUlJSHD6mZYlZVuw3fNoCcr5CVm5YgcClWMyweQb8MMxqvAa2hue2F8N4VTgQGcPvR66SYZKxkECKejNunld44643iJwcydIhS4XxKhAInEKR9ajBgt5kwWiW0Zus/08zCE1aGBMnTsyhSRs0akyjps0ZO+EF9u3bZ3/YvuCz+Q5pUht5jR+cp0ltfW/bto1Ro0bZNakkScyYMQPIHVFc2TWpQFDuSYiEQ0utxqtaC83uh2aDSmi8KiRnmIiIS+XLf8/z7LKDdPlwM51nbWbk0oN8sjGcdSei7carXn2QD/qNY/ezu4Xx6kJE5KuLKMh8tRXdihDmq8sxmGTcdDkjX2VFIc1optX0f1w+ntPv9cdT5/jX8tdff6VZs2Y0bdqUp59+msmTJ/PGG2/YReu6det48MEHeeutt/j+++8xGo2sX78egJUrV9K2bVuee+45xo4dW6RxpqSkMGLECD7//HMURWHu3LkMHDiQ8+fP4+NTeH6a+Ph4dm/bwlvvzsTLyyvX+9mnTalUKhYsWEBYWBiXLl1iwoQJvPrqqyxcuDDXdlmRHjlvGLZs2YK7uzvbtm0jMjKSUaNGUb16dWbNmmVf57vvvmP8+PHs3r27wL5fe+01Jr49m46dujB//nzeffddwsPDuZqQjlmlyxU5LcuyXeRu374ds9nMxIkTeeyxx9i2bZt9vYsXL7J69WrWrl1LQkICjz76KB999FGOMZZXTJlRr1q1Kt8iaiLyVVBmJF2F30dDVOZDnU6jof+HoHUvUjOxqTf568RlUtP9AAmjFInOM5zedbvx2cMfUC+onvPHLhAIqjQZJgst3t1YJn1XFU2akJDAxo0bmTVrll2TWrIVLvP39+fWTavJKUmSw5o0P5ypSW19d+/ePYcmBfKMuK0KmlQgKLcoMkTshMuZ32uvmtByqDXdQBExmC1ExKVxM8VAbLKBm6kGDGYZS4b1IYnaw3rtkySoW01Hgvk/otL3YFRdpG1IDb578Eua1mjqrD0TOIgwX11EhtFqTtxecAsg1Bb5ekuYr67GYJZBJ+XI+QoVJ/XAkiVLePrppwEYMGAASUlJbN++nV69egEwa9YsHn/8cWbOnGnfpm3btgAEBASgVqvx8fEhKCioSP326dMnx/L//vc//P392b59O/fff3+h21+6dBFFUWjStPCL/uTJk+3/Dw0N5YMPPmDcuHF5Cl2NrcDEbadPp9Px7bff4unpScuWLXnvvfd45ZVXeP/991FlRmQ2btyY//u//yu07+fHjWPi27Nxd3fDz88PSZIICgrC4p7BrVRDrs/Oli1bOHHiBBEREYSEhADw/fff07JlSw4ePEjnzp0BqyBetmyZ/UbhmWeeYcuWLRVC6NrzveaTcgBEzldBGXFuI6x6HjISwM0XBn8GrR4qQgMKlxMvsz3iP27G10JDdRRkdB4R9G0UQvOa95CRkoy3rmTTSgUCgaCiU3E16SUURaFZs6y837aCW7YHyrZ/n5/4IgFe1ui0wjRpfjhTk9r61ul0OTRpflQFTSoQlEuSb8CplWCMsy7XbguN+4Kq6IWtkjNrDqQYzDleV0lQzUvLXY1r0qlpPVoE+7Dr+i+8s+1V0kxpeHh4MPueD3nhjhdQq3J7UoLSR5ivLkJvzjvnK0BoDWue18u30l06pqqOLCuZppEaiaxp6xZZQadWcfq9/i4fU16fj/wIDw/nwIEDrFq1CgCNRsNjjz3GkiVL7EL32LFjRY4gcISYmBjefvtttm3bRmxsLBaLhfT0dK5cueLQ9nKmAZdflGR2Nm/ezOzZszl79izJycmYzWb0ej3p6el4eubMkZzdQM9O27Ztc6zbrVs3UlNTiYqKon79+gB07NjR4b4zMtLx8M0ZTWErbnG7+XrmzBlCQkLsIhegRYsW+Pv7c+bMGbvQDQ0NzRGhUbt2bWJjYws9PuUBe77XfFIOQM7IV0VR7JEwAkGpYDFZ0wzs/cK6XLsdPLIUAho4tLnJYuLQ1XBOxqdiNASgojkaQJLM3NnYnU4h/XFdFkWBQFBV8dCqi6RHL8elk2IwEezvwY0kPbKi0CTQG52m6DfaVUWT5pVeQZZz5s61Xe23/buZL+fPdUiT5oezNWlR+q4KmlQgKHec3wwrRkPyXeDtA00HQK3iTfVPNZj447DVePV2U9Ogpje1fNyo6eNGdS839KlJTOjdiAQSGL1mGNsvbwfg7np38+2Qb2kU0MiZeyYoIsJ8dRF6oy3tQG5zwpZ2ICo+HbNFRlNA9JjAeRiz557MVFU281VWwMutfH89lixZgtlszlHMQFEU3Nzc+OKLL/Dz88PDw6PI7apUqlxC1GQy5VgeMWIEt27d4rPPPqN+/fq4ubnRrVu3HDmrCiIktAGSJHH+fHiB60VGRnL//fczfvx4Zs2aRUBAALt27WL06NEYjcZcYtMe+erQKHJye/qDgvo2GU25jN7sOYOLg1ab88mnJEl2k7q8Y498LcB8teV8lRUFi6KgEearoLRIuAy/PwvXDlmXu4yDfu+Bxq3AzRRFYX9kNHP+/Zf9p5LAUh21Rz1UgIRMvepu9Gkaiq9H0aMUBAKBoDhIklSkqf9uWhUmWY23mwYPnRqLrOCu1eSZ9syZVGRN2rBhQyRJylHo1XaLoMrUdiqVxLWoKzz5yEMOa9KSUBRN6uy+oWJrUoGg3GAxwdZZsOtTyFDAqwZ0egI8AorVXJrBzO+Hr5KsN+PnoeHhjiF43+5XKDKLDi5i1qFZZJgz8NJ68VHfj5jQeQIqSXhMZU35dpcqEQXlfA30ccddq0JvkrmakEFojdw5MAXOx2DKEhE2G6ikBpqrMJvNfP/998ydO5d77703x3tDhw7lp59+Yty4cbRp04YtW7YwatSoPNvR6XRYLJYcr9WsWZMbN27kiE48duxYjnV2797NwoULGThwIABRUVHExcU5PH4fvwC69+zD118t5pWpU3KJzMTERPz9/Tl8+DCyLDN37lz7VKxff/0133bValvagZzn7/jx42RkZNiF/759+/D29s7x5P92Cutbo1LlOH72z85tfTdv3pyoqCiioqLs/Z0+fZrExERatKgcCc6N2XK+5odKlRVZbrYoFODTCgTF58xa+HMC6JPA3Q+GfAnNB+e7uqIonLyWzC+Hz7Hq2GXSMjyAamDRoGDGzyuDzvWCaRoYIB6MCgSCco9NvkqShIQEKMV6IF0UKromrVatGvfeey9ffvklL774Il5eXnYtp5YkEhMTUaHjzIljRdKk+VEamhTyPn63UxU0qUBQLki6ag0EiNpvXW7/NGgeK77xajTz+5GrJGWY8XHXMKxD3VzG6630OP44+QtnMxaAJ/QO7c2SB5YQVi2spHsjcBLiTsJF2MzXvKbwqFQS9QMyi26JvK8uw5YKQqXKqqqa39Tx8oYtAf7o0aNp1apVjr9hw4axZMkSAKZPn85PP/3E9OnTOXPmDCdOnODjjz+2txMaGsqOHTu4du2aXaj26tWLmzdv8n//939cvHiRL7/8kr///jtH/40bN2b58uWcOXOG/fv389RTTxUpokFWFN78YA6yxcIdd9zBH3/8wfnz5zlz5gwLFiygW7duADRq1AiTycTnn3/OpUuXWL58OYsXL8633fzSDhiNRkaPHs3p06dZv34906dPZ9KkSXYBmxeF9a1WS4SGhpKamsqWLVtIir9FRkZ6rs9O3759ad26NU899RRHjhzhwIEDDB8+nJ49e9KpUyeHj1l5xpHIV8iKfjVZRPSEwMmYDfD36/DLU1bjtU5HeH5nvsbrqetJfLzhLN0++ofBX+zih72xpGV4IKNH5XGM+zvFM7J7GCO7tqFlcA1hvAoEggqBbM9Vav2DvKfVO5OKrkkBvvjiCyzZNOnF8+e5dD6cbxZ/Sbdu3ZBUEiGhYUXSpPlRGpoUyKFJ4+LiSE/Pnc6uKmhSgaDMCd8Ai++yGq9uvvDId3DvByAVL+4xw2Rm5eGrJKab8HHT8HCHuvi4Z0WnK4rMnqg9LD78FddSruGl82LRoEVsHr5ZGK/lDHE34SL0pvwLbkFW3tfIOGG+ugpb5Gv2IkGaChL5umTJEvr27Yufn1+u94YNG8ahQ4f477//6NWrF7/99htr1qyhXbt29OnThwMHDtjXfe+994iMjKRhw4bUrFkTsD4VX7hwIV9++SVt27blwIEDTJs2LVf/CQkJdOjQgWeeeYYXX3yRWrVqOTR2RVGQFYW69UPZf+AgvXv35uWXX6ZVq1b069ePLVu2sGjRIsCaF2vevHl8/PHHtGrVihUrVjB79ux829ZkCtfb7zPuueceGjduTI8ePXjsscd44IEHmDFjRoHjLKxvjUqie/fujBs3jscee4wG9YJZtmhBrs+OJEn8+eefVKtWjR49etC3b18aNGjAL7/84tDxKu8oioLJbN3nggpuQc68rwKB04iPgCX3wn7rdYNuk2DUBqhWP9eqepOFN1f+x6AFu1i07SI3kszI6ElT7aJG8GrmPq3lwrtvMGvQ47hrRHoBgUBQsZCzFYqS7OZr6fZZkTWpjQYNGnDkyBG7Ju3f4w6ef/Ihdm7fyqJFi1BJ0LRFa6bP+thhTZofpaFJgRyatGbNmrkKdkHl16QCQZliNsLGt+Cnx6yFXoPbw/M7oOXQYjeZkGZk7fFo4tNNeOnUDOtYJ0f6q5vpN1ly9Fs2XdqEWTYT6h/K7md3M67TOJFmoBwiKaX9OLSccfXqVUJCQoiIiCA0NNRl/faes42IuDR+G9eNzqG5w81n/32Gr7ZfYkS3+swc0spl46qImEwm1q9fz8CBA3PlJCoK52NS6PfpDprXdGPewDqEhYVxK0PmVpqRWr7uBPm6O3HUAhsWWebU9WQAWgb7oi7gSX9RScowcflWGp46DY1qlU718cu30kjKsBazqOGdlUNSb7JwLiYFjUpFi2DfUum7vCDLMsnJyfj6+mKWFc7eSEGSJFoF+xZYSCsqPp2EdCNBfu7U8hHfr6Kg1+uJiIggLCwMd/eSHztnXUfLnFOrYc0LYEgGj2owdBE0vS/PVc/FJDB86Q5uJGpQkElX7SVDs4sBLUN49a6XuKPOHfZ14+PjWbj1Al6+/oUOIS05kQm9GxEQULypZMUlMjKSsLAwoqKiqFu3rkv7FjiHstKkAufg7OuoM67zp6OTMVtkGtfyISohHb3JQoMaXni7V+DrfCmSXc9kjzw9F5OC3mQhrIYXPu5abiTriU3WU91LR51qzs2vKigZ+Z1DQekhNGke5Ko3MB76zbTXGyiKrgSrtnyqSz3Gfn+Y8JgUfPz8eaRjXfw9dQDImdGu2yK3YVEsuKnd6N+wP028QpnQu7FLNanQo44jcr66iAxj/mkHAMKqW9MORN7KPUVEUDoY7BXas86Jbdq6XM4jXysythnnEs6vFW6LXDaXYlEAW2SrpoCCW9lzk1V2jPaoV6nQfRaRrwKnYdLDP2/BwW+syyFd4eEl4Jdb9CXqE3n1r5/ZeKQGkuKBhURSPb9keOfOTO76nZiSJRAIKg2KnJV2wPaLLH5xi47tPsCWjswm+cTtgUAgyEWuegMLofn9JWrSaLEwfsURwmNS8NCqGNYhy3iNTYvlz/A/uZ5yHYBGAY0Y3GQwvm6+pCUnlnRvBKWIMF9dREEFtwB7ka1IkfPVZRgyc75mz1Npi8I0C3VVatimxJWGN+mKgmm2z8bt+WVtAl1BQVZAXTW8V3u+14KKbdkQOV8FTuHWRfhtBNw4YV2+awr0fgvUOaMlIhMjmbf7c37db8Ld2B8JkLXhjOwpM/XOdVTzqOb6sQsEAkEpYUvrBDnrGVStOY7OwZLtOII1jQOUfv5cgUBQgTAbYNO7sD8z/3KdTvDIUvCvV6JmjWYL6/6LJjbFSDVPLf1aBBLgpUNWLOy6spsdl7djUWTcNe4MaDiAtkFtcH5Ik6A0EOari9DbCm7lk/M1LNN8vZqQgckiO2RkCEpGVs7XrIuVK8y7qo7t2JbGJ1zjguhTSz7mq+1GR1EULLKMWpX3d72yYTQ7VmwLROSrwAmc+B3+egmMqeBZHR78HzTum2OVQ9cPMWfPHFad3EWA4RXclUYA3N08ncWPj8fLrWiFWAQCgaAioChZUa4qiWw5X8VvblFQFCUr8jVT60ki8lUgEGQn/hL8Ngqij1mXu78A90zPFQhQVEwWmdXHrhObYsTPQ8Pipzvy79lYbqTe4M/wP7mRegOAJtWbcH+T+/HR+ZRwRwSuRJivLkCWFfsUd/d8DIpaPm54aNVkmCxExafToGbp5KsUZFFQ2gFhvpYeroh8BWuEqtbJ4adWYzXvtAO2/s0WpUp9fmxRrI6Yr7aHSqZSTAshqKSYMuDv1+DId9bl+nfCsG/ANxiw5r5af349c/bMYfvl7XhauhNonIcKL7zc4IsnOtG7WWAZ7oBAIBCULnI2k1WSJHsclPjFLRpyNhM7K+1AZloyYWQLBIJTq2DNi5n1BgLgwcXQpH+Jm7Uar9eITtKjU0t89XQnGtRy5/1Nu9l/6wiyIuOh8eC+xvfRulYrRLRrxUOEV7oAfeb0dsg/8lWSJOpXtyZwF6kHXEPeaQeE+VraZFXidX7bkiSV6jmUlazx51UoTCNVvc+PPfLVgWj97JGvIhJH4DA3w+HrPpnGqwQ9XoXha8A3GL1Zz9eHv6blwpYM/mkw2yN3U930PDWNb6LCi071q7F5ah9hvAKLFi2iTZs2+Pr64uvrS7du3fj777/t7+v1eiZOnEj16tXx9vZm2LBhxMTE5GjjypUrDBo0CE9PT2rVqsUrr7yC2WzOsc62bdvo0KEDbm5uNGrUiGXLlrli9wSCKo9NekiShCrzD0TagaJii3qVkOyBAip7FHEZDUogEJQ9Jj2snQq/jbQaryFdYdwupxivZovMmuPXuZ5oNV7vbxOMQbpEn+/6sDtqN7Ii07xGcyZ0nkDrWq0RxmvFRES+ugBbsS0Ad03+U5HDanhx9kYKEXGi6JYrMORhGgnztfTJXnCrNNCoJCxy6USf2tq03tjkft/++alC6txYlMjXTMNaVhQsimI3qwWCfDn2E6ybCqZ08KoFD/0PGvYmLj2ORQcX8cXBL4hNiwXAX9OQMOl94vW+ADzfswHT7m0q0vhkUrduXT766CMaN26Moih89913DBkyhKNHj9KyZUumTJnCunXr+O233/Dz82PSpEk89NBD7N69GwCLxcKgQYMICgpiz549REdHM3z4cLRaLR9++CEAERERDBo0iHHjxrFixQq2bNnCmDFjqF27Nv37l/zmRCAQ5M/tD7dF2oHiYbE/ZMeevkoSka8CQdUm7oLVdI2x1RuYmllvoOR2mlmW+eu/61xNyECrknigXW3+u7qFL5a/hqzIBGo6cn+Lh2hZswXCdK3YCPPVBegzTT43jcqeuD0vbEW3LovIV5dgz/mazTTKHrlYlSrWu5LSjHwFW0SqXCpF0yyZ0+XV2QpZ5Oy7apn3ipIt7YADBpdKZY1MtsgKZouCA36toKpiTIP1r8CxFdblsB7w0DecNybz6boJLDu2jAxzBgAhviE8UP9ttv9Xn3i9GT8PLfMebcs9zUW0a3YGDx6cY3nWrFksWrSIffv2UbduXZYsWcKPP/5Inz59AFi6dCnNmzdn3759dO3alX/++YfTp0+zefNmAgMDadeuHe+//z6vvfYaM2bMQKfTsXjxYsLCwpg7dy4AzZs3Z9euXXz66afCfBUIShnFrq8yDUNshUAFRcFemyCbUFVhM1/LZEgCgaAs+e83WDs5s95ADXjoK2jUt9DNHMEiy6z7L5or8RloVBJ3NtXx5/nviLl1FVkjM6TZEFp6jqZGQLBT+hOULcJ8dQG2yFd3bcEFeMKqW83XiDhhvrqCgtIOVLWK9a4kazpX6ZBVdMv5Wc7MBeR7hapnvtqMV1W2dA+FoVGpsMgWzBYZCrkmOoKsKCSkGfF116IVbm7lIOa0NbogLhwkFUrP19kT2o0568fx59k/UTKthA61OzD5jmlcimrN0t2XATPt6/nzxZMdqONfdYpqpaSkkJycbF92c3PDzc2twG0sFgu//fYbaWlpdOvWjcOHD2MymejbN+tmolmzZtSrV4+9e/fStWtX9u7dS+vWrQkMzDK1+/fvz/jx4zl16hTt27dn7969OdqwrTN58mTn7KxAIMgXm/Swm68i8rVY2NNLZXvIrhLHUiCoehjTYcNrcOR763Lo3fDQ1+Bb2ynNK4rC+hM3iLyVjloFdWpF8+f5rSgoeGk8+XzoMgY3HczCrReK1b4syyQmJjq8vr+/P6o80uoJnIcwX12A3mQ1+TwKMRpska8i56tr0JtyR+xJEtkq1isOG0oCx7GUeuRrZl7RUkw7kN/noqqZr9lTDjgaJa5VSxjMYHLSMYpPM3I9MYM0Twv1Ajyd0qagjFAUOLoc1r8K5gwU7yB2dBrO6xdXs2/76/bVBjUexLTu02jg05kXfz7GsajLAIy5K4xXBzRzKAVGZaJFixY5lqdPn86MGTPyXPfEiRN069YNvV6Pt7c3q1atokWLFhw7dgydToe/v3+O9QMDA7lxw1pZ98aNGzmMV9v7tvcKWic5OZmMjAw8PKqOKS4QuJr80w6U0YAqKHlFvkoqEfkqEFQpboZbAwFiTwMS9HwVer4GqpIHjtjYdSGOS3FpqCRQ3A5xPO4cAK1rtaZnYDcGN21dovYTExOZt/Yo7l4+ha6rT0th6v3tCQgIKFGfgoKpWncoZUSGzXzNp9iWjdDMglvXEjLsRWwEpUdeka85CzZV3XMwY8YMAgMDkSSJ1atXO7Vt22EtrYuPWiVxcO8uAn097E/7li1blsNUmDFjBu3atSty25YSRL726tWr0kV/GS3W/XQk5YANW/5NW9RsSUkzWIv96LPl1hZUQAwpsPI5WPMCmDO4UqMRXTRGem1/m31X96FT6xjTfgynJ5xm7ZNrSUlqwqAFuzgWlYivu4b/PdORt+9vUeWMV4DTp0+TlJRk/3vjjTfyXbdp06YcO3aM/fv3M378eEaMGMHp06ddOFqBQFBa2MzX3HlKy2xITqE0NWle2B+0Z498zfy3OJGv27ZtQ5Ikp2vSklAZNalA4DSO/Qj/62U1Xr1qwfDV0PtNpxqvp64nceRKIgCp0i7iTefw0XnzeKvHeaj5Q7hrnPOw2t3LBy9f/0L/HDFoBSWn6t2llAG2yNfC0g7U9HHDS6dGVuBKvCi6VdpkFdzKaaRVlIr1I0eORJKsuUd1Oh2NGjXivffey1V5uqicOXOGmTNn8tVXXxEdHc19991X4rFmF5ZZNwd5r5ucnMxbb71Fs2bNcHd3JygoiL59+7Jy5UqHRG9exuhjjz3GuXPnij1+G2YHIl8P7t1F3QCvXNM8Vq5cyfvvv1/iMZQnbA+JimJ4aTK/b2aLc75ftrQuBossCmFUVG6csIrcE79iQWKmRiI07ggHkyIJ8Ajg7bvf5vLky3z9wNeE+jXh9T/+44WfjpJiMNOxfjXWv3Q397YMKuu9KDN8fHzw9fW1/xWUcsD2W9GxY0dmz55N27Zt+eyzzwgKCsJoNOa6bsXExBAUZD22QUFBxMTE5Hrf9l5B6/j6+oqoV4GglLE/3LZFvma+rrgg62tF1aR5YU87oJLsmrRN65Z0bhREz/ZNiqRJ88JZmtQRbjd+bVRGTSoQlBhjGqwaD6vHWwu9hvWEcbugQS+ndnMtIZ0tZ6zFYvXSfxhVV2gb2JYJnSfQtHpTp/YlKF+ItAMuICvna8EGhSRJ1K/uxenoZCLj0mhUy9sVw6uy2M1XTU5TvCJNHR8wYABLly7FYDCwfv16Jk6ciFarLTDyKT8sFguSJHHx4kUAhgwZUioFx+zTufJoOjExkbvuuoukpCQ++OADOnfujEajYfv27bz66qv06dMn17TY28nLGPXw8Cjxjb/RaCw87UABx6syTuMwmR0vtmVDo3Je5KvJIttTHyiKgtEsF/qQS1COUBQ49C3yhtdRWYxEofAEaey2WGgY0JCp3aYyou0IvHTWlDxnopN54aejXIhNRZJgYq9GTO7bGE0RPn+CnMiyjMFgoGPHjmi1WrZs2cKwYcMACA8P58qVK3Tr1g2Abt26MWvWLGJjY6lVqxYAmzZtwtfX1576oFu3bqxfvz5HH5s2bbK3IRAISg/59oJbLk47UBE1aZ59Z8qTlJQk7hvUj6SkJGa+9x7V6jdHrdEQffaIw5o0L5ylSXU6XbG3r4yaVCAoETGn4bcREHcOJBX0ehPunurUaFeAuNR0Vh69goIao3QZncdlHmr6JI0DGju1H0H5RNyxuIAMB3O+AoSJvK8uw5B5Xm43jtQqCRQFiyHV+gTMlX9FVMhubm4EBQVRv359xo8fT9++fVmzZo11/wwGpk2bRp06dfDy8qJLly5s27bNvq1t2tOaNWto0aIFbm5uPPvss/aK2CpVzjye33zzDc2bN8fd3Z1mzZqxcOHCHGO5evUqTzzxBAEBAXh5edGpUyf279/PsmXLmDlzJsePH0eSJMJqevPnrz/mWXDrzTffJDIykv379zNixAhatGhBkyZNGDt2LMeOHcPb2/pAYvny5XTq1AkfHx+CgoJ48skniY21PkHMK/L19ileNr766itCQkLw9PTk0UcfJSkpyf7eyJEjGTp0KLNmzSI4OJimTZtikRX++uNn7ut9V559X426zJhHrcevWrVqSJLEyJEjgdxTvBISEhg+fDjVqlXD09OT++67j/Pnz+ca88aNG2nevDne3t4MGDCA6OjoPI5c2ZA956ujaJ0Y+ZpxW6oBWyoRQflH0ScR890gWDcVlcXIWky0IxU55A5+f+R3wieFM6HzBLx0XiiKwvK9kQz5cjcXYlOp5ePGitFdmNa/qTBei8Abb7zBjh07iIyM5MSJE7zxxhts27aNp556Cj8/P0aPHs3UqVPZunUrhw8fZtSoUXTr1o2uXbsCcO+999KiRQueeeYZjh8/zsaNG3n77beZOHGiPdp23LhxXLp0iVdffZWzZ8+ycOFCfv31V6ZMmVKWuy4QVFwUxWENKRvTkEzpqC0ZYExDZU5HMqULTVqAJlWr1fz44485trWZ2P/3/gy7Jh05YiQNmzQjtEEjxowZ47AmzQtnadLC+o6MjKR3795A1dCkAkGxUBQ4/B183dtqvPrUhhF/Qc9XnG68Xkq4wooDZ5EVNWZu0SRYz4TOE4TxWoUQka8uwNGCWwChNax5X4X5WvrYI1+1KiArCk+tkpDMGQR81tz1g3rzOmRGeRUHDw8Pbt26BcCkSZM4ffo0P//8M8HBwaxatYoBAwZw4sQJGje2XuTT09P5+OOP+eabb6hevTq1a9emV69ejBo1KoegWrFiBe+++y5ffPEF7du35+jRo4wdOxYvLy9GjBhBamoqPXv2pE6dOqxZs4agoCCOHDmCLMs89thjnDx5kg0bNrB582YuxaWicfPKFfkqyzI///wzTz31FMHBwbn2zSZyAUwmE++//z5NmzYlNjaWqVOnMnLkSNavX+9wkbQLFy7w66+/8tdff5GcnMzo0aOZMGECK1assK+zZcsWfH192bRpE2BNO2A2mXnznel0atsqV9/169Vj7v++5+XnhhMeHl7gVNuRI0dy/vx51qxZg6+vL6+99hoDBw7k9OnTaLVa+/mZM2cOy5cvR6VS8fTTTzNt2rQcYyxLbOartkjma2bkqxNyKqffbr6aZBAzm8s1JouJzbvn0Gr7HEIsZkwovIGByOaD+Kv7NLqHdM+xfmK6kdf++I+Np6xT2fs0q8UnD7ehunf+U+sFeRMbG8vw4cOJjo7Gz8+PNm3asHHjRvr16wfAp59+ikqlYtiwYRgMBvr375/D0FCr1axdu5bx48fTrVs3+/X/vffes68TFhbGunXrmDJlCp999hl169blm2++oX///i7fX4GgUmBKhw9za6K8qJn5ZyMw86/YVAFNKstyrohai6wgyzJ//vGbXZNmTzEgK45rUkcpjiYtrO+QkBD++OMPhg0bViU0qUBQZAwpsHYKnPjNutyoLzz4FXjVcGo3KYYUpm54mY0n2uDm0QQFPQNa1aBlYFen9iMo/wjz1QXoTVaTwb2QglsAodUzI1/jRM7X0saQY8p0TvO1oqEoClu2bGHjxo288MILXLlyhaVLl3LlyhW7kTlt2jQ2bNjA0qVL+fDDDwGraFu4cCFt27a1t2V7Gm/L4QfW6tlz587loYceAqw32KdPn+arr75ixIgR/Pjjj9y8eZODBw/apzI1atTIvr23tzcajYagoCCSSMFgtuSKfI2LiyMhIYFmzZoVur/PPvus/f8NGjRgwYIFdO7cmdTUVNRujrlver2e77//njp16gDw+eefM2jQIObOnWvfdy8vL7755hv71K4LsSk8+PjThFb3wtdDm6tvnZsHfv7VAKhVq1a+09FsAnf37t107241m1asWEFISAirV6/mkUceAaznZ/HixTRs2BCw3rxkNzrKElnJSiFRpLQD2SJfFUUp0TTCjGzR60aLjF4UKiy3JBuS+frQ/0ja+Qlv6TNwQ+IyCr+1uI9xfWfRKKBRrm0ORMQz+eejXE/So1VLvH5fc569M9RlU08rG0uWLCnwfXd3d7788ku+/PLLfNepX79+oYZCr169OHr0aLHGKBAIKj4VSZPKskxycnKO8VtkhYT4WyQmZmlSSZJQSRKyouTK9VqQJs1u0hZEcTSpI33b9r+ya1KBoMhE/we/j4JbF0BSwz3vQPeXQOXcGVWbLm5izF9jSIrqgQ+1AZmHO9SnbjVfp/YjqBgI89UF2AwCd40jka9W8zUiTkS+lja2Kcp5pR1QNB5cm3CROv4uDqPTehZp9bVr1+Lt7Y3JZEKWZZ588klmzJjBtm3bsFgsNGnSJMf6BoOB6tWr25d1Oh1t2rQpsI+0tDQuXrzI6NGjGTt2rP11s9mMn58fAMeOHaN9+/YO5ZDKykmW8/WiFC44fPgwM2bM4Pjx4yQkJCBnRlFeuXKFxk2zzNuC2qxXr55d5II1V6Esy4SHh9uFbuvWrXOIXLOscPq/Y7z+5RxOnviv2H2fOXMGjUZDly5d7K9Vr16dpk2bcubMGftrnp6edpELULt27QKnsrkSm8+pUamK9MBCmylqZEVBVpQC8+QWhKIopButhTz8PXXEpujtqUQE5YeopCgW7F/Ar4f/x6cGEw+hBSTO1mhErSd/Y1pAg1zbWGSFL/69wGdbziEr1nQ8nz/RnlZ1/Fy/AwKBQFCWaD2tEagOcD0pg1upRmr5uBHo605cqoHoJD3+HlpCAoqmL+19F4GKqEnzwqIoeaZckCRAsT58zk5BmtSWD7swiqNJndV3ZdCkAoHDKAocWgIb3gSLAXzrwMPfQj3nRqEm6ZOY9s80vjn6Dd7mfvibBwEwsFUwdav5OLWviobFYmHGjBn88MMP3Lhxg+DgYEaOHMnbb79tD7BQFIXp06fz9ddfk5iYyJ133smiRYvsMyUA4uPjeeGFF/jrr7/sM7c+++wzhx96lQXCfHUBtryEHrrCn6TYIl+vJ2WgN1lE8ZhSxGDKO1+lWiWBJGFWe5RoupUr6N27N4sWLUKn0xEcHIxGY/1Kp6amolarOXz4MGp1zs9Q9guSh4dHoVFkqampAHz99dc5hBlgb7sohQNs0ZK3d1uzZk38/f05e/ZsgdunpaXRv39/+vfvz4oVK6hZsyZXrlyhf//+GI3GHEZgSYumeXnlPP8pqamMf3qYY307ocKFbaqXDUmSil1d19mYM4eh0xTNPFWpJNQqCYusYLIoFDdlp9EsY5GtkbP+nlqr+WqWSxxNK3AOR6OPMnfvXH459QvtLTLb8CQMLRZJjdxvJs26Tcp9EQCikzKY/PMx9kfEA/BQhzq8N6QV3m5CrggEgiqIJDmsRWW1hKLVIOncQeeOpNOgaFVYNFqX6NmKqEnzQpYVqlWvgd9tmlQlSVhQ7EEEULgmdSa3a1JX9g3lW5MKBA6hT4I1L8Lp1dblJgNg6CLwdG4Bur/P/81za5/javJV3CytqGF+ATNpdKpfjcaBVdt4Bfj4449ZtGgR3333HS1btuTQoUOMGjUKPz8/XnzxRQD+7//+jwULFvDdd98RFhbGO++8Q//+/Tl9+jTu7u4APPXUU0RHR7Np0yZMJhOjRo3iueeey5XHuzwh7mZcQFFyvtbw1uHtpiHVYCYqPl18QUsRe9qBvMxXSm7cuQIvL68cU6lstG/fHovFQmxsLHfffXeJ+ggMDCQ4OJhLly7x1FNP5blOmzZt+Oabb4iPj88z0kCn02GxWFCULNF6u+emUql4/PHHWb58OdOnT8+V9zU1NRV3d3fOnj3LrVu3+OijjwgJCQHg0KFDWe1Ikr3tgs7hlStXuH79ur2fffv2oVKp7EUMbkdRFC6eO0diQjyzZ88mLLR+nn27ZUYlmEzmfPtu3rw5ZrOZ/fv326d43bp1i/DwcIcjFcoaW+SrthjuqUalwiJbMFtkKOYDpuyFDN001kIcsqJgssjoHJhlIHA+iqKw4cIG5u6dy5aILaDAFHT8H55oAKVaKOqHl6Ku0yHP7S/eTOWRxXuJTzPipVPzwYOteLB9XdfuhEAgEFRQsmYWWXWsPYLIRf1XNE2aHxZFQaVS8fAjj7JixQq7JlXZI7Ic16SOUlRNCjjUty1StqD9rQyaVCAolGtHrGkGEiJBpYG+M6HbxDwDAYpLQkYCUzZO4bvj3wHQwOcOPJKnk6oo9G8ZSGj1YsxAqITs2bOHIUOGMGiQNRo4NDSUn376iQMHDgDW+4n58+fz9ttvM2TIEAC+//57AgMDWb16NY8//jhnzpxhw4YNHDx4kE6dOgHWdC0DBw5kzpw5edaPKQ+IMsEuoCjmqyRJ2YpuibyvpYneni8y50W3Ipmv+dGkSROeeuophg8fzsqVK4mIiODAgQPMnj2bdevWFbm9mTNnMnv2bBYsWMC5c+c4ceIES5cuZd68eQA88cQTBAUFMXToUHbv3s2lS5f4448/2Lt3L2C9qEZERHDk6FES4m9hNBjy/K2bNWsWISEhdOnShe+//57Tp09z/vx5vv32W9q3b09qair16tVDp9Px+eefc+nSJdasWcP777+fox1HzqG7uzsjRozg+PHj7Ny5kxdffJFHH300R16x7JhlhaA6ddHqdCz88ot8+64bUg9Jkli7di03b960R2lkp3HjxgwZMoSxY8eya9cujh8/ztNPP02dOnXsPzLlnazI16L/jGgzv3OmEnzHbMW2PHVqJEnCLXMcthzbAtdhMBtYenQprRe1ZuCPA9kSsYUaqDnk04h5uFuf8rYYgvT8DsjHeI1PM/LssoPEpxlpXtuXtS/eLYxXgUAgKAK2n1RbykLbZJyyjk4sr5r02LFjxMXFYTAYcrQvZx7I997/IIcmvXjuLJcjLvLdsqVF0qSOUFRNCjjUd/369auEJhUI8kVRYN9iWHKv1Xj1qwfPboTuec/AKi5/hf9Fy4Ut+e74d0hITOo0jfrKR6TqFdrW9eO9Ia0gV8WTykVKSgrJycn2v9uvrTa6d+/Oli1bOHfuHADHjx9n165d3HfffQBERERw48YN+vbta9/Gz8+PLl262K/je/fuxd/f3268AvTt2xeVSsX+/ftLaxdLjDBfXYAtQsvNwQivrKJbIu9raZIV+ZrzvNhyUFZk8xVg6dKlDB8+nJdffpmmTZsydOhQDh48SL169Yrc1pgxY/jmm29YunQprVu3pmfPnixbtoywsDDA+mT9n3/+oVatWgwcOJDWrVvz0Ucf2aeADRs2jAEDBtD3nnvo1bYRG/78I8+fn4CAAPbt28fTTz/NBx98QPv27bn77rv56aef+OSTT/Dz86NmzZosW7aM3377jRYtWvDRRx8xZ86cHO3YohPMBZzDRo0a8dBDDzFw4EDuvfde2rRpk6Oy9+1YZIWA6jWY9elCfv/993z7Dq5Th/FT3+Cdt98iMDCQSZMm5dne0qVL6dixI/fffz/dunVDURTWr1+fa1pXecWS6XEWpdiWDVu0rNlSfKM0u/kK4J5pvtpyOQtKn/iMeD7c+SGhn4Xy7JpnOXXzFN46bxa0fIpo74Z0TIkFtRsMmguPfAfueedsNZgtPL/8EJdvpRMS4MEPo+8grEb5TvkiEAgE5Y1cka+Zr5eHmeHlUZP27t2bwMBA/vjjD3vbiqLY9U2N6tVzaNKh/e5i1LCB/PbrL0XSpI5QVE0KONR3nTp1mDlzJq+//nql1qQCQZ5kJMAvT8OG10A2QbP7YdwOqNup8G0d5Fb6LZ5e+TQP/PwA0anRNKnehO0jd5Ic8wiXbqYT5OvO/4Z3qhKpJFu0aIGfn5/9b/bs2Xmu9/rrr/P444/TrFkztFot7du3Z/LkyfbZDDdu3ACsMx2yExgYaH/vxo0b1KpVK8f7Go2GgIAA+zrlEUkp68ehLubq1auEhIQQERFBaGioS/p84aej/HX8Ou/e34Jn7wordP25/4Tz+b8XeLJLPT58sLULRlixMJlMrF+/noEDB5ZIFNz76XbOxaTy06gO+MuJhIWF4e7ujsFkITwmBbUk0VIUeHEqepOFczEpqFUSdTwVfH19UTm5qiTApZuppBrMhFTzpJqXrvANHCDNYObizVR0GhXNgvKvUHkxNpU0o5l6AZ74ezqn7/KGLMuE30jGJFuLIfm4F+17GJ2Uwc0UAzW83QguRlE7WVE4dT0ZRVFoGuiDm1ZNTLKemGQ91Tx1xSssUs7R6/VERETYr1MlpSTX0UsJl5i/bz5Lji4h3WSdoVHHpw4v3fEik8wWPLZ/AooFAhrCI8ugdv4FVBRFYeqvx1l19Bo+7hpWTehOo1pln24nPj6ehVsv4OXrX+i6acmJTOjdqNjFXYpLZGQkYWFhREVFUbeuiBKuiJSFJhU4D2fpURslvc5fiE0l3WimfnUv/Dy0JGeYiLyVhqdOQ6Na5bcASVkiyzLJycl2PSrLCievJwHQMtgvRy7/izdTSTNUbn1XEbn9HApKn/KkSfPl6iH4bRQkXQG1Du79AO54zqnRrqvOrGL8uvHEpMWgklS83O1lZvaayScbIvh2dwTuWhW/Pd+d1nX9iqQrIUtbAsXaLiAgwGVa1qZHT58+naNwoJubG25ubrnW//nnn3nllVf45JNPaNmyJceOHWPy5MnMmzePESNGsGfPHu68806uX79O7dq17ds9+uijSJLEL7/8wocffsh3331HeHh4jrZr1arFzJkzGT9+fJH3wxWInK8uIKvglmNPPOqLyFeXkBX5KkG2vPT2KeuKIor3OJmcURml99xHkym+Cop8LSq2tjSFCLvKkLbCEcwliHy1n59iRr7qTdb8wWqVZE974GaPfBVpB0qL/Vf3M2fvHFaeWYmsWI9z28C2TOs+jUdD+6Bb8yJc2GRdudXDMHg+uBVspH7+7wVWHb2GWiWx6KmO5cJ4FQgEgopIlsayLkvlJO1ARcJWLFUi6zjasEUUV3J5JxBUbBQF9n4Bm2eAbIZqodZAgOD2TuviZtpNXvj7BX459QsALWq24NsHvqVL3S78dOAK3+6OAGDeo+1oXbfqBHL5+Pjg65t/gJKNV155xR79CtC6dWsuX77M7NmzGTFihD3dSkxMTA7zNSYmhnbt2gEQFBREbGxsjnbNZjPx8fEFpmspa4T56gJs02AdyfkKEGbL+SrM11LFkJkbUqtR52m+gtVA06iF+eosbHm01KVsaKvVNgPUeUaczUxV367Gb+87m3lfXjCYLUhIxcrPmhdmWbFb59qS5Hy1FO8YZdhTDmjsD0ds03kMmcaseGjiHGRF5q/wv5izdw67ruyyv96/YX+mdZ/GPWH3IF3eA1/3gZRo0LjDff8HHYYXGl2w5vh15m2y5nv6YGgr7mpco1T3RSAQCCoz+RXcEmah49i0nkol5dIR5SWHrkAgyIf0eFg9Hs5tsC63GAoPLMg37VVRURSF307/xqT1k7iZfhO1pOa1O1/j3Z7v4qZxY+/FW7yz+iQAU/s1YWDr2oW0WDVJT0/PFaWuVquRM+/bw8LCCAoKYsuWLXazNTk5mf3799sjWrt160ZiYiKHDx+mY8eOAPz777/IskyXLl1ctzNFRJivLsBmFLhrHTMpbDlfryfp0ZssVSJHSFlgM8V1alWOGExJklBLEhZFyTRfy2Z8lRGb11bas4I0qsJzvhYVm5GrcdR8LSd3OxZZ5kJsKhLQJNAHTTEiVW/HlBmxqlWr7Dd5RcGW89VUTHPclu81+wMtnUaFhPV7a7YoaDXCfC0JGaYMvjv+HfP2zuN8/HkAtCotT7V5iqldp9I6sDXIFtgxB7Z9CIoMNZpYowsCWxba/uHLCUz77TgAz/VowBN3FD3vn0AgEAiysP2k5sr5WoozjSobNgM7ryCBrMhXcTwFgnLHlX3w+2hIvmqtNzBgNnR61mlpBmJSY5iwfgIrz6wEoHWt1iwdspSOwVbjLzIujfErDmOWFQa3DeaFPo2c0m9lZPDgwcyaNYt69erRsmVLjh49yrx583j22WcBqxczefJkPvjgAxo3bkxYWBjvvPMOwcHBDB06FIDmzZszYMAAxo4dy+LFizGZTEyaNInHH3+c4ODgMty7ghHmqwuwFdxy1EQN8NLh464hRW/mSnw6TQLFNMzSwDY92U2jQn/be2qVhMWilBsDrbJgi3wtjmFXFErDADUXNfK1nHx20o0W+1ji04zU8i15biajLWVHMY1cuzluKV5qj4zbim2B9TOl06gwmC3ozZZiReQKIDYtloUHF/LlwS+JS48DwN/dn/GdxjPpjkkE+2QKmtRYWDkWLm2zLrd9AgbOAbfC8wpGxafz3PeHMJpl+rUI5LUBzUppbwQCgaDqcHvagaxIzTIaUAUke+Tr7dikSjmRdwKBAKxPnXbPh38/cLjeQFFQFIWfTv7EC3+/QHxGPBqVhjfvepO3eryFTm3N/RwVn87IpQdITDfRtq4fnzzcRszAK4DPP/+cd955hwkTJhAbG0twcDDPP/887777rn2dV199lbS0NJ577jkSExO566672LBhQ44cwytWrGDSpEncc889qFQqhg0bxoIFC8pilxxGmK8uwGa+Opp2QJIkwmp48d/VJCLi0oT5Wkpk5Xy1mq/ZpxGpVRJYytfU8cqApYCIAmdSKpGvloppvqYZLPb/x6UaqeHtludNRVEwZh6L4qYxsEXfyoqCrChF+jxYZBm9Oe882m6Z5qvBLFPZrpqlPc0xPC6ceXvn8d3x7zBYDACE+ocypesUnm3/LN66bKbqpe3wxxhIiwWtp9V0bf+UQ/0k6008u+wgt9KMtAz25bPH2xX6nRIIBIKqRHGu90rm7ylkGYe2m38hZR2noPRYKvvxFAdUULUpN9+BtDhY9Txc2Gxdbv0I3P9pofUGHCU6JZpx68axJnwNAO2C2rF0yFLaBbWzr3PyWhKjlh3kZoqBOv4efD28k5i1XAg+Pj7Mnz+f+fPn57uOJEm89957vPfee/muExAQwI8//lgKIyw9hPnqAmy5RR0tuAXW1AP/XU0SeV9LCbNFtptjnm5uJGPNP+LhYa28Xt4MtMqCXEBEgTMpzcjXwtIOaMrZZyfdaLb/3yzLJKQbqe6du/JkUbBFvmqLmQ9ZrcpK7WGyKBQlgNYW9apTq+zpC2y4a1Uk6615Xysb6enpAM6rAotVPO+8spP5B+bz17m/7K93Du7MtO7TeKj5Q2hU2WSCbIHtH8P2/wMUqNncGl1Qy7HIVZNFZuKKI5yPTSXI150lIzrjqRMyRCAQCCDr+p5djzpKdi/EXnDL9p5IO+Aw9iABEfkqEORLaWjSIhO5yxoIYKs3MPATaP+MU9IMKIrC98e/Z/LGySTqE9GqtLzT4x1ev+t1tOqsfd59IY7nlx8m1WCmWZAP3z17h1NmGAoqL+KuxwUUNe0AQGj1zKJbt4T5Whpkr4ju4a7F39/fXjHP09MTxWxEMZvJyFDhrhLV052FwaBHMRuRTQpGyYRer8+VcNsZWIxmFLMRk6xCr3eOMDAa9ChmCxaTCr0+f+VtNplQzEaMWNDry/YSqygKqekZKIqCn4eWpAwTMQlmPNVyiabD6PUZKGYLWFTo9cVrRyWbMVsspKWng5vj5ygpzYBiNqJVa9DrcyYMkWTrsU/LsKD3qBxpBxRFIT09ndjYWPz9/VGrS/403Syb+fX0r8w8P5Pzx635XCUkBjcdzLRu07ir3l25Px/J0dY0A5E7rcvtn7EW1tJ5Orwf09ecYuf5ODy0ar4Z0YkgPyFQBQKBwIZarc6lRx39rTZbZBSztXqs0WBAkiSMZguK2YhFknL9XgqsyLKM0Wi061G93mjVqWYFvT7n763FZH3PaFCKrX0Ezuf2cygoPUpDkxYZ2QI758K22Zn1Bppm1hto4ZTmryZf5fm1z7P+/HoAOtbuyNIhS621DrKx5vh1Xv71GCaLQtcGAfxveCd83cvQjBZUCIT56gIy8igOUxihNaxFtyJE5GupkN181alVBAUFAdgFb0K6kTSDBb2HhkRxIXUaielGUg0WMtw1aBUTHh4epZITxyzLxCYZkCRQpRUteiQ/YpL1mCwKSrKOWwV8l41mmdgUAxqVhJJStuaSbSwqCTR+7txK0mNRICNelyNfalG5kaTHLFuPRUIxp9bcTDFgMMuYk7RFin68lWogwyRj8NBiTMy5nW1/1RJYkpxz3ssL/v7+9utUcUkxpPDt0W/5dN+nXE66DIC7xp0RbUcwpesUmtZomveGF7bAyucgPQ60XjB4PrR5tEh9L9kVwY/7ryBJsOCJ9rSq45zKswKBQFCZuF2POopZVohN0iNJoMuw/v5ZbK8B2vTK9ZvoLBRFISMjw65HkzNMJOvNpLupMSTocqybojeRlGEmVacmI16XT4sCV3P7ORSUPs7QpMUiJcYaCBCx3brc9kkYNAd0XiVuWlEUvj36LVP/mUqyIRmdWsfMXjOZ1n1azllgWDXt+2tPAzCodW3mPdYWN1GhW+AAwnwtZRRFKV7ka6b5evlWeqmMq6qjN2VNXbZNga9duza1atXCZDLxz46L/HowmmEd6jKhd1hZDrVS8dHfZ9h0OpZn76xPUFoUPXr0KJUpK+lGM+NW7wLgrxfucsrU5mmL9pCYbmTxMx0Jq5V/LqEr8WnMWHMQLzcNaybdVeJ+S8Kqo9f4YmsUnUMD+GhYA3btieD7vZdpWNObr57pWCyRarbIPLdgJ7KssPzZzgRXK57g+WndabacjeW5uxvwWBEq3b/+1V7iUg18+lg7wur653gvw2hmwufW8/7H+O74e1aOmyOtVlui6IJrydf4/MDnfHX4KxL1iQDU8KhBX7++zH1sLsH++VQFtZhh6yzYNc+6HNjaGl1Qo2gVXDedjmHW+jMAvDWwOf1aBBZzTwQCgaByI0lSDj3qKJdvpTFjdU7tkZxh5PnVewD4Z0pPkV87D0wmEzt27LDr0S+2nmfVkVgev6MeY1vm1P9WTXWeHk1qMn1wPg8rBS7n9nMoKF1KqkmLzaVt8MfYrHoDg+ZCuyed0vSVpCuM/Wss/1z8B4AudbqwdMhSmtdsnmM9WVb4eONZvtp+CYAR3erz7uCW4toqcBhhvpYyOaa3FyHSLKy61dCITtKTYbQUaVtB4djOi9ttBYPUajVqtRqdzp1rKRaupVhyVNUTlIzoVOsxVWvdMJvNuLu7l4pQcnNTuJmhYDTLpFtUBJTwHCqKQvhNa7RndV/vAj8T1X0lrqVYIMWCVudWpj/IeyKTuZZi4bGgari7u/Nol4bM33qZa5eSOBiVSo8mNYvcZlR8OlFJZtSSQp0AH9zcimdwenh4cC3FwpVks8PfsRtJeo5Hp6NWSbSqVwP320x1d3eQNDquJmRwJclMUIBvscZWWTgRc4K5e+fy44kfMcnWm/gm1ZswtetUnmjxBFs3baWmVz6fgaRr8MdouLLXutzpWej/IWiLFj118loSL/18FEWBJ7vUY/Rd4mGWQCAQFIZNjzqKUTFwLcVCkKS1/6ZaJI1VjwAqjQ53cS+RC7VanUOP3kiVM3WqLpc2UWt0XEuxEJMmi3uDcsTt51BQybi93kCtFtZAgJolfwCiKAr/O/w/pm2aRqoxFXeNO+/3fp8pXaegVuW8XposMq/9/h8rj14D4NUBTRnfs6GIthYUCWG+ljL6bIVf3ItQGbyal86eo/FyfBrNgqq2ieBsDJnV0t20eZ8TPw/rj3dShuNRB4LCSTNYj7u3W+leeiRJopqnlphkA4npJupWK1l7qQazveBWtUKiKX09soRfcoaJal5lF3155HICAJ3qWw9ANS8dj98RwtLdkSzadrF45muCNRo/wK1khdNq+liLfsUkO56H7lhUIgBNAn3yjWZuVMubqwkZnI9N4Y6wgGKPr6KiKAqbL21mzt459if4AHfXu5tp3adxf5P7UUmqfCOqzt5I5t81P/Dk9Q/xJwWzxgvVkC9QtX6oyGO5kaRnzHeHSDdauLtxDWY+0FKIVIFAICgFbMU1s6cU0mW77zBaZDwQ5mthpOqtx9Enj5RjtnsGfSUs6ikQlEuSo61FtS5bZ7XRYTgM+NjhegMFEZEQwZi/xvBvxL8A3BlyJ98O+ZYm1ZvkWjfNYGb8iiPsOHcTtUrio4da80inkBKPQVD1EOZrKWNLOaBVS2iKUtIba+qB41GJRMYJ89XZGEy2yNe8hai/p818NbpsTFWBFINV1Hrr1BhKua9qnjpikg3Ep5X8HCamW40qN42q0Ch0rVqFl05NmtFCUhmar9FJGVxLzEAlQdsQf/vrY+5uwPK9l9l76RbHoxJzvOcIV+MzAKjuVrJyv4GZ1UBjUxz/JBy/mghAu5D884U2ruXNtvCbnI9JLdH4KhpGi5GfT/7M3L1z+S/mPwBUkoqHWzzMy91e5o46dxS4/ZnoZL7YfIbW4QuYoFkLwAk5lIlpL6Ff48uQK6d5qENdmtd27LcozWBm9HcHuZGsp3Etb754sgPaIv4GCgQCgcAxbPcb2TWKJtsDUqNZFI91hBSDVe/5uue+Rbalj8sQ5qtAUPpc2Awrn7fWG9B5w/3zoc0jJW5WVmQWHlzI65tfJ82UhofGg9n3zGbSHZNyRbsCxKUaeHbZQf67moSHVs3CpzvQu2mtEo9DUDUR5mspYyu2VZR8rzZCq3tyPCqRiDiR99XZ5Jd2wIaIfC0d0jLNVy83jUvMV7AWTyspNgM3wEEj1c9Dazdfy4rDmVGvzWv74pUt0riOvwcPtAtm5ZFrLN5+kUVPdyxSu/bI1xLOuKuVGfkaW4TI1+OZka9tb8v1mp1GtbwBuHizapivifpEvjr0FQsOLOB6ynUAvLRejOkwhpe6vERYtYKn+Z+OTmbh9ghOnjrJ57rP6aC5AMCVRs+w0utZkk/EkZhi4OudEXy9M4JmQT481KEOQ9rVsRvot2ORFV76+RinridT3UvHtyM726+pAoFAIHA+eRX3lSQJnUaF0Sxjsgjz1RFS7JGv+ZuvepM4lgJBqWExw9YPYNen1uVi1hvIiwvxFxi9ZjQ7Lu8AoEf9Hix5YAmNAvJu+8qtdIZ/u5/IW+kEZOrZdkUMWhEIslPmYShffvkloaGhuLu706VLFw4cOFDg+vPnz6dp06Z4eHgQEhLClClT0Osdv3l3NbYfaI9ima/WvK+RcWlOHZMgK+2ArhDz1RbxKHAOtulcpZ12AKCal/POoc3AdbSAk285MO8P35ZyIDvjejYEYMOpG0U2KaPireZrDSdGvipK4W3JssJ/V5MACozWbZRZDK2yR75GJkYyZcMUQj4N4fUtr3M95Tq1vWsz+57ZRE2JYv6A+QUar6euJ/P1WRVDFu5DPrOO9W5v0EF1AYvOFx5dTr2nv2D6gx048GZf/vdMR+5rFYROreLsjRQ+XH+WbrO38MyS/aw6etU+3dXGR3+fYfOZGHQaFf8b3omQgJJPDxMIXEFl16SCyku6MXfkK1gLy4KIfHWUFLtOzf3A0HYvZxCRrwJB6ZB8DZYNyjJeO4+BMZtLbLxaZAvz982nzaI27Li8Ay+tF1/c9wVbR2zN13g9eS2JhxbtJvJWOnWrefD7uG7CeBWUmDKNfP3ll1+YOnUqixcvpkuXLsyfP5/+/fsTHh5OrVq5w7l//PFHXn/9db799lu6d+/OuXPnGDlyJJIkMW/evDLYg8KxTU0pTuRrWI1M8/WWMF+djS3tQH7nJSvtgDBfnUlW5Gvp5x2zGaXOTDtQzdOx6L3y8Pmx5XvtkIf52iTQh77Na7H5TCxf77jER8PaONxuVII17UCJI199rZGv6UYLqQZznvnVsnMpLpVUgxkPrZrGmdGteWGLfL2RrCdFbyq03YrGoeuHmLNnDr+d/g1ZsV7HWtVqxbRu03ii9RPo1AU/IPjvaiKfbT7PlrOxaJF5V/MDz2o2WN+s0xH1w99CtVD7+jqNintbBnFvyyCS0k2sPXGdVUeucehyAjvPx7HzfByeupMMaBnEQx3qEnkrja93RgDwycNt6JjH508gKI9UBU0qqLykZ95veN5uvmpUYEBEvjpIit6q2/KOfBU5XwWC0iIw6Riab16CjARw84UHFkDLB0vcbnhcOM+ueZY9UXsA6BPWh28Gf1NggMKu83E8v/wQaUYLLWr7smxUZ2rlM9tLICgKZWq+zps3j7FjxzJq1CgAFi9ezLp16/j22295/fXXc62/Z88e7rzzTp588kkAQkNDeeKJJ9i/f3+x+o9N1nM8M3/HXY1rFH9HCsD2A12syFdhvpYajqYdMJhl9CZLsczz0sAiKxyLSqBVHb9889WWVxRFIdWYlXagtAnINF8TnZB2wBb5WlixLRv2yOkyMl8zjBZOXU8GoFNo3kWnxvVsyOYzsaw8co0p/ZrkO4X8dmyRryXN+eqp0+DjpiHFYCY2xVCoSXosyhr12rqOX4H5s/08tNTycSM2xcCF2FTa16v45p+syKw7t445e+fYp0oB9GvQj5e7vcy9De8ttJDVsahEPtt8jq3hNwGoL8WwxGMBjWSrUUq3SXDPdNDk/xn389TyVJf6PNWlPpdvpbHq6DVWHb3G5VvprDx6zV4BFmBqvyYMaVenBHstELiWstakAkFJ0OeRdgCsNScgS/cKCibZgbQDFT3nqywrHLuaSLOg/IuXCgQuw2JCtWU6XS99aV2u3Q4eWQoBDUrWrGzh032f8s7Wd9Cb9fjofJhz7xzGdhibr2ZO0Zv4dlckX2w9j8mi0L1hdb56pmOlC+QQlB1ldsU1Go0cPnyYN954w/6aSqWib9++7N27N89tunfvzg8//MCBAwe44447uHTpEuvXr+eZZ57Jtx+DwYDBkJVdMiUlBQCTycSOc7FM+/0EXcOq0SU0/wIuJSElw9q3m1bKt7p0ftT1s94ExyQbSErLED+QmdiOY1GPZ3bSDVYzTafO+7y4qRTUKgmLrBCXnO6wMVXaLN93hffWneWlPg2Z1LthWQ+nSKQZzNhml7uprP8pyTksDF93q0i+lWoocT+3UvT2Nh1pyyfTXE5I1ZfqPubH4ch4zLJCoK8bNT3zHnPbOj50rOfP4SuJfL3jIq/1z13d83b0Jou9QFZ1t5Kfv5o+OlIMZq7Hp1HP363AdY9ejgegdR2fQvttWNOL2BQD4dFJtKqdf5RseUdv1rPixAo+3f8p5+LPAaBRaXisxWNM7jKZtoFtATCbzfm28d/VJD779wI7zt8CQCXBO2HnGH5zDmpTKoq7P5bBX6A0GQAK4OA5DfbVMbFnGBN6hHI0KonVx66z/uQNkjLMDG1bm3F31y+Tz76zMJlMKIoFWS78JltRLJhMJpfvb0U+vuWN8qBJxfmseDhDjzqLFL1V17ppVDnGYyt0mGEwlotxljeyn0ODWbanZ/BQ5z6vaqzv6U2WCn0sN5+JZfyPx3iic13ee6BFWQ+nxJSn76GgiCReQb1qLOrrhwEwdRwNfd8DjZvDejQvTt88zXPrnuPAdWvqoH5h/Vg0cBH1/OrlqZnTjWaW74vim12R9sCZQa2C+HhYK9zyuBYUh6LoSsjSlrb/F3U7258rtKz47jlOmbl5cXFxWCwWAgMDc7weGBjI2bNn89zmySefJC4ujrvuugtFUTCbzYwbN44333wz335mz57NzJkzc72+Y8cOEnU1AA0Xo+NZv359ifYnP47GSYCa9OTEYvXhpVGTZpZY8ec/1PFy/vgqMps2bSr2todirOcl8dbNfM+Lu0pNmizx1z//ElxOUhbuuqwCVKw5eIEGGeFlPZwikWQE0CChsGvbv0hSyc5hYVy+aT3H569cZ/36qyVq6/gl63G/df0K69dHFrr+rWjr+sdOnWN9Wt7Xs9Jk0zXrvtfWZvD333/nu14HT4nDqFm+N4KGhgt4FvKLEJMBoMFNreCpKfn5Uxutx+mfnfuJP1twJO2OU2pAwnLzEuvXXyxwXU16Zrv7T+Bx43iJxlgWJJuT+Tvub9bHrSfJbI349VR50r9GfwbVGEQNTQ2uHb7GNa7l24ZZhr+jVGy5LqEgoUKhWw0Db2pW0PL6FgBueTXmcOh4Mi7IcKFkv4FdNdCpDdzIgGCPKP7+O6pE7ZU1KSkpXLymwt3Lp9B19WkpbNJfxMen8HWdSVxcnEv7q8yUB016+vTpku2EoMwoTS3jKKcy9WHMtZw6xZhh/e3cuXsP133LanTln02bNpFiAtut8Y5/N6G6LTjOpmP1Jgvr1q2nkAkn5ZZ/rlo14q7TUazXRJb1cJxGefgeChwnKPEw7a98jcqSjlHtydF6Y7khd4R/thS7TYtiYVXsKn6+8TNmxYynypNn6zzLPb73cHL3SU5yMsf6RgvsjpHYfF1Fqsn6hQ70UBhQV6a991W2/FOy+8fsFEVXQpa2BIq1nY+Pj8u0rNCjjlOhQim3bdvGhx9+yMKFC+nSpQsXLlzgpZde4v333+edd97Jc5s33niDqVOn2pevXbtGixYt6NGjByrfWnx+ahfJZjX33Vf4tM3ikHHkGpw/RZ3AWgwc2KHI238btZ/jV5Oo27wD97UKcvr4KiImk4lNmzbRr18/tNriTQOI23cFLp2lXp1gBg7MO9/l/HO7iLiVTttO3egcWj6mLh9ZfxauX+Fahpp77u2Xb9qE8khEXBoc3o23u5Z77+1T4nNYGJ7nbrLiwlE0Xn4MHNitRG398+t/EHODTm2aM7B7/ULXv7z9ElujL1A9OISBA1uWqO/isGr5ESCOQV2aM7Bb/uMdICts+3IP52PTiPNrxrieBU/x2X7uJhw7SmgNbyQpqcTnb3Paf5z/7wbBDZsz8K7QfNczmCy8vP9fQGHk4F7U8fcosN2EA1Hs/OsMik/xrrtlxblb51hwYAHfn/0evdkabV3Ptx4v3PECo9qOwtfNsTvnizfTePn3/zh13RpVN7hNENM6qqn37ySkmBMAmLpMYrehA33vva/UvoMVmfj4eCJ2XsLTx7/QddNTEul3dwMCAvJO8VFaREZGurQ/QU6crUlDQ0NdNHKBs3CGHnUWh9aegetRNG/SkIF9G9tfX3RpD7H6VDp07sKdDauX4QjLJ9nP4bVkIxzajZebmvsH3Ztr3RS9iXcPb0VBom//ARVKg2fn8LqzEHWFVEXHwIG9y3o4JaY8fQ8FDmA2oPr3PdQRXwEgB3fEMngRNw6cLdE5PBl7krHrxnI42hpFe1/D+/jyvi+p61s317oGs8zvh6+yaHsEMZkz+kKqefBin4YMblMb9e1PXpxAUXQlZGlLoFjbBQQEuEzLCj3qOGVmvtaoUQO1Wk1MTEyO12NiYggKyttkfOedd3jmmWcYM2YMAK1btyYtLY3nnnuOt956C5Uq94+gm5sbbm5Z01mTk615ELVaLbWrW6ejGswyaaas6ujOJLOuE55ummJdTBrU9Ob41SSiEg3iB+U2tFptsY+J7by46/I/L36eOriVTqpRLjfHXlasPwZGs8y5m+l0qED5LPWZMx68s30XSnIOC6OGj9WgS0w3l7gPWw6w6t7uDrVVzdvdvp2rPzvWXF7WaMk7wmoU2v+4no14+bfjfLcvirE9GxWY3/h6snVaY0g1TyCpxOevtr81pDwuzVRgOyeiUzHLCjW8ddSv4VPog7KmQdY0Mhdvppeb725+KIrCnqg9zNk7hz/P/omCNQK4Y+2OTOs+jYdbPIxG5dhPtaIo/LDvMrPWn0FvkvH31PLRQ60ZoOyGP14CYyp4VocH/wehPVHWry/V72BFRqvVIklqVKrCc2tLkrpMjqM4b86jPGhScT4rLuXh/OnN1t8Ob3ddjrHoMn/TFVRlPsbyjFarRW+2Tp31dc/7fHpLWb8HFqXiHs+EDKumTUg3kWGx7m9loDx8DwWFEB8Bv42E6GPW5W6TUN0zHY0iAWeLdQ5NFhMf7fqI93e8j0k24e/uz2cDPuOZNs/kul8wWWT+OHyVz/+9wLVEawHhOv4evNCnEcM61rWnaSkNiqIrIUtb2v5f1O1sf67QsuJ75zhlZr7qdDo6duzIli1bGDp0KACyLLNlyxYmTZqU5zbp6em5xKxanSkqlKIXf3HTqKnhrSMu1cj1pAyqeTlWTKcoZJSg4BZAaHVrroHLouiWUzFkuq9u2vwvsuWhYv3tZK9We+RyQoUyX1MNriu2BVnFsRKcWXDLwQc0toJbZfHZuRSXRmK6CXetihbBhUdKPtAumLn/hHM9Sc8fR67yVJf8I2VtxbbqVis48tRRavlYTQhbHtn8OB6VCEDbuv4OzVBoHGh9sBaVkF6uCuZlxyJbWHV2FXP2zGH/tawCPfc3uZ9p3abRo36PIs3GuJli4NXfj9sLat3duAZzhjYhcM8MOLzMulL9O2HYN+AbXKJcWgJBZaM8aFKBoCSkZ95veOpy/t7pMs0EUXCrcFL01t/FvIptgbV4mUoCWQG92YIfFdNwiMumuaLi02kZXDp1TwSCHJxaDWteAEMyeFSDoYuh6QDre8XUpMduHGPUn6M4duMYAA80fYDFgxZT26d2jvUsssKfx67x2ZbzXL5lvZcJ9HVjUu9GPNo5pMIVsRZUXMo07cDUqVMZMWIEnTp14o477mD+/PmkpaXZK80OHz6cOnXqMHv2bAAGDx7MvHnzaN++vX2K1zvvvMPgwYPtgreoBPm5E5dq5EaSvlR+fPSZJp+7rpjmaw1rZFhkXLrTxiQAg9kqUguaMlSWBlp+mCxZN3SHLycw5u4yHEwRSc2MHvV2lfma+TAl3WjBYLaU6Ic1Ic36GfD3dOwBTdZnJ/9CSKXF4czCVG3r+jv0BFerVjHm7ga8t/Y0/9txicc718t3uk1UvPUpcd1qHpBQ8rHWyixkF5OsL3A9u/ka4u9Qu9W9dPh7aklMN3HxZmq5urFINaay9OhSPt33KRGJEQC4qd0Y3nY4U7pOoXnN5kVuc/PpGF774z9upRnRaVS8cV8zRjQ2ovplEMSeAiToMQ16vg7qCpVtSCBwGeVBkwoExUVvzNt8temA7A/vBXljm+WUX2VzSZJw16pJN1rQmxwrflMeuZVWtczXa4kZGM0yYTVE8ZQywaSHf96Cg99Yl0O6wsNLwC93OgBHMVqMzNoxiw93fYhZNhPgEcDn933OE62eyBG4IMsK605EM3/zOS7etAay1fDWMa5nQ57uWr9cBmcIKjdlehf22GOPcfPmTd59911u3LhBu3bt2LBhg73gwZUrV3JEFbz99ttIksTbb7/NtWvXqFmzJoMHD2bWrFnFHkOQrwcnryUTnVTwzX9xsUW+uhfT+LH9UESIyFenYosAKMiQ8y+X5muWeD50OQFFUUolV3FpkGZ0rfnq665BrZKwyAqJ6SYCfUtgvmZGvgY4aL7aPjvJZfDZOXzZ6op2rO94VPTjd4Sw4F/r0+C/T0Zzf5vgPNeLSsiKfDU4wXwNzIx8vVlY5GtmGgVHzVdJkmhcy5uDkQlciC0f5mt0SjRfHPiCRYcWkaC3HrwAjwAmdp7I/7N33uFRVQkb/01N76QBoSNFeo8ooqKoqLio23RVVFAEC2XXsq51P911wbI2bGBZddeOIioIAipNeu+QBEhPJmV6ud8fd+4kQMr0mcD5PQ/PwyR37j1TMnPue9/zvtOHTyc7MbuVPZyOyebg79/s4cP1hQD0zknixd8PplfpN/DmLLAbISETJr0J3dt+rptAEEqiYU4qEPiLyS2+niom6N0mA5twvrZKa85XkFcyyuJr230+K+obVoQVVp3Z5p6dx2v47etrUQHrHr6kWWFdECIqD8Ent0CJ3DfA+TPhor+Cxv/XYdOJTUxeNJkdZfI+r+tzHa9c+cpJ82hJkli6u5Tnl+1nb4ncf5Aar+POMd255bzOxOuFEUEQGSL+zpsxY0azS7pWrlx50m2tVstjjz3GY489FrTjt0+VnVfFNeag7bMxZvdkKE7vX4ZIZ3fsQHmdlXqrI2zC1ZmOL85Xgyl6xFeHq2GyV15n5Vi1mbz0+AiOyHvqrfJzHq73sEqlIjVOR6XRRrXJRrbbZekrVofTc1KT5qPz1RCEyANf8Ud8jddruSW/Cy8uP8D8VYeY0D+3SVFfiR3IS4vjYBDG6o3z1WCyyWVtwMCO3ouoPRqJr5FkV9ku5q2dxwc7PsDmlN8PPdJ7MGvULG4ZdAvxOv/+frcVGbj/f1s9z83UMd2YPbYDMUsfgK0fyBt1HSMLr0mirFEg8IZIz0kFAn9piB04eY4lnK/eU+fFCi1F3G6rzleH03VSHNeZLL4eqzYx+Z1fPXP4/aX1Ps2NBQGy41P4+pS+gZ7j/N6d1WHliVVP8Owvz+KUnLSLb8erV77KDefe4NlGkiRW7i/n+WX72e42biTFaLnjgm7cdn4XIb4LIs5Zr+TlpCjia2icr5YAM19T4nSkJ+ipMto4WmGkX4fIO7jOBJTM15aWG6S4hbZocr7aHCfnyG0urG474qslvJmvIF/lrDTaqDL6L4Iq4rta1bIbojGK+Gq0ObE7XSENcG9MtdHmWVbjax7wLed14fXVh9h5vJafD1ZwQc/Mk35fY7Z7luR1SA2S+Op2vppszmYvLimu167tEryOfQDokZUEwIHS8IuvkiSx4sgK5q2dx7cHv/X8/Ly885idP5uJvSai8TI4/1QcThevrTzEi8sP4HBJ5CTH8txvB3JecjksvBTK94JKLUcMjJkDfh5HIBAIBG2H5mIHFJOBTYivrVLXSuwANHRFmNuo+FplstE4krqwKjTmo0hTY7YzeeGvJ62sOlQuxNewYDfDtw/A5nfl253Pd/cN5LZ8vxbYcHwDkxdNZnf5bgB+d+7veOmKl8hMaDhXWXOognlL93tMKPF6DZNHd2HqBd1JiReiqyA6OOvF1/YpcnFMSYjF10AyRbpkxMvia6UQX4NFQ+yAF87XKBJfFeeCkme5qaCaiYM6RHhU3mG0Ko6C8IlB6Ql6DpUbA3IvKw6B1Hg96mayUE8lOa7hS77WbCcjMaaFrYPH5kJ5wtE9M8HnAsH0BD2/H96Jd9YcZf6qQ6eJr4rrNSNBHzQBPSFGS2KMlnqrg9JaC4mZiadt01C25dtnX48seV8Hy8Mnvtqddj7e9TFz1871hP+rUDGpzyRm588mPy8/oP0XVZmY+b+tbHRPLCcMyOXpif1I2fc/+O+fwWGGxBx5ktu1DQVCCwQCgSAgTHZ5jnXq+YZOI89bROxA6yixA8ktXGhXYuTaqvO1ou5kM0LRGeh8tTqc3Pn+Rg6U1ZOTHMvAvBS+31XKoTDOB89ayvfBJ7dC2W7kvoE/w4UP+N03YLabeWzlY8xbOw+X5CIrIYvXJrzGpD6TPNtsKqhi3tL9rDlUCcjn9jfnd+auC7uH7fxLIPCWs158DbXz1RwM8bVdApsLDZ52PkHgeGIHdM2Lr57M1wgsHW8OJXZgRJd0lu4u9VzdawvUK+Krl+7RYKA4JasDeA0byra8v2qqUatIitFSZ3VQE0bx1Z/IgcbccUFX3l9XwC8HK9l+zMCAjqme3x1T8l6D7LTOSo6hvtxBWa2V7i2Jr17mvSr0dIuvRyuMIXcf11hqeGvzW7yw/gWO1R4DIF4Xz+RBk5k5aibd07sHtH9Jkvhs83Ee/2qXxyH85MRz+c25KagWT4cdH8sbdr9YXtaVmNnyDgUCgUBwRmFuxvmqF85Xr2lwvraQ+apXxNe2+XwqZVtJsVrqLA6OVZtwuqRmi1bbGpIk8cCn21l3uIrEGC0Lbh3OxoIqWXwtE/0pIWXrR/DNLLCbICELJr0RUN/AmqI13LboNvZV7gPgxv438uLlL5IRnwHAjmM1zFu2j5X7ygH5QtMfR3Ti7ot6+B01JxCEmrNefM1Nach8DUV5kdn95exv7ABAV3fuq5LtJwgcbwq3lCUK0RQ7YHfHDozslsHS3aXsKa7FaHWEdSm/vyjiazjHmuZ+DasDih2wufflm5M0JV7nEV/DheKIHNY53a/7d0yL55qB7fliy3HmrzrEqzcO9fyuyL00rVOwxdekGA6XGymrO/0CmCRJbDtmAHwXX3NTYknQazDanBRUGj0xBMGkqKaIF9e/yBub3qDOJgf6Zydkc8+Ie7hr2F2eCWIgmG1O5nyyjW92FAMwvEsaz/12EHm2Q/DGRKg8CCoNXPxXGD0T1OGJuBAIBAJB9GBqRnz1ZL6eElslOJ06q1K41fzF9li3aUMxcbQ1Kupl8fXc9slsKqjG7pQoqbXQITUuwiMLDvOW7ufLrSfQqlW8euMQ+rZP9hgwDgvna2iwGWHJnxv1DVzo7hvwvUgWwGQ38ciKR3hh3QtISOQm5vL6Va9zda+rAdhbUsvzy/bz/a5SQDa83DC0IzMu7kHHtLYRxSc4e4l+xSbEKFdGLHYXBpPd56W6rWHxFG4F5nwF2cElCA5K5mtLsQOp0Rg74Ha+5qXF0SE1juMGM9uKDJzXo12ER9Y6DbEDYRRfExTnayCxA/J903zMC0qJ03Gs2hy294/d6fK4RIcEkGl154Xd+GLLcb7dWcKRCiNd3Z8/RdUNZVvBRPkMLqu1nva74wYzFfU2tGoVfXOTfdqvSqWiR1Yi247VcKC0Pqji65biLcxbO4//7fofDpf8vu7Trg+z82dz44AbidUG74r7c8v28c2OYrRqFTMvPYe7xnRDs+Ud+PZBcFohqT1cvwA6BxZpIBAIBIK2iSRJnpV2p5o9GpyvbVMsDCfeOF+V2AHFadzWqKyXhcispFg6pMZxtNJEYaXpjBBf/7fxGC//KDcSPD2pP2POkVcBKauqCqpM2Bwuz99ENLHzeA2JMVrPOX+boXS3HDNQsU/uGxj7EFww2+++gZ8Kf+LOJXdysEp+HW8ddCvPXfYcaXFpHCqv54UfDrB4+wkkCVQq+M2gDtx7Sc+297wJzlrOevE1VqchI0FPpdFGcY0l+OKrI7DCLYAubufr0UohvgYLT+yAF5mvtWY7Lpfkdd5nKFEyX3VaNUM6p3HcYGZTQXWbEF/rIyG+BiN2oFHmqy80fv+Eg10narE6XKTG6+ie6f8kpHdOMhf3zmLF3jLeWH2YZyb1BxpywYJd8KaUbpXWnu583VYkl231yU32K7qlR1aSLL6W1XNFYMNEkiS+O/gdc9fOZcWRFZ6fX9TlIuacN4fLe1yOWhXcCX1hpYl31xQA8OqNQ7isezx8fjvs+lzeoOdlcO18SAjcYSsQCASCtonV4fKUKJ1q9tArzlencL62hjeFW8pcpK1mvpa7na/tEmPIS4/naKWJomoT+bTtecTuahVvrd8DwH2X9OS3w/I8v8tOjvGshCqsCs1KqEAoqbEw6dU1ZCbF8PMDFwV9FW5IkCTY8j4s+UtD38D1b0OX8/3aXb2tnjeOvcGSrUsA6JjckTeueoMrel5BYaWJv3+9jS+2HMPl/hib0D+X+8f1pGd2dL2WAkFrnPXiK8i5r5VGGyW1Zvq2981d1RrKldGWskVbo0s7WeyoqLdRZ7G3OCkQeIeS1RTTgqCjlCa5JKizOjxiWiRxuCfPeo2aoZ1S+XrbCTYVto3c17YfO+C78xXCF1vhyXvtlBbwxO2uC7uzYm8Zn206xsxxPclKjqWoWo4dyAvykh7F+Vpad7rzdWuR/JgG5vlXNOgp3Srzf6mZ1WHlgx0f8Nza59hVvgsAjUrD7/r9jtn5sxmSO8TvfbfGs9/vxeZ0cX6PdlyaVgyvT4bqI6DWwiWPQf4METMgEAgEZzmmRi7MU80eSuyAKNxqHaVwq0XnqyK+ttHnU3G+ZiTqsTrk+VxbL93adaKWhfvVOF0S1w3pyP3jep70e5VKRfesRLYfq+FgWfSJr1uLDNicLo4bzBytNHlWnEUt1jpYPKtR38Al8JvX/e4bWHFkBXd8dQdHDEcAuGPwHcy9bC4nqlXc998tLN5ejNOtuo7rk83MS3tybntRQC5omwjxFchNiWPXiVpOGIJfutXcMiBfSIrV0S5RT0W9jYJKE/06iA+cQPHG+Rqr0xCrU2Oxu6g126NCfFUKE7RqFUPduZ6bC6qjxpnbEkrsQFJEnK+Bxw746nxVCrpqAji2L2x2i6+BRA4oDO+SxtDOaWwqqGbBL0d54PJensKtvPTgLk3L8sQONO98HZTn32NSSrcO+CG+VpmrmL9xPi9teImS+hIAkvRJTBkyhXtH3kvn1M5+jclbNhdWs3h7MSqVxL86rUf19lPgtEFKHly/EPKGh/T4AoFAIGgbKOcaeo0a7SnlkqJwy3u8ih1wm2naqvNVyXzNTIxB6z5vKGzD4uuxahNT3t+MzaXivG7pPDOpf5MGhO6Zsvh6KApzX/eW1Hr+v63IEN3ia8kOOWbA0zfwCIy+3y8jQJ21jr8s+wvzN80HIFOXyTvXvUO6biT3fdRQpAUw5pxMZl16DoN87H8QCKINIb7SULpVUhN88VX5cg4k8xXk6IGKehtHKoxCfA0CDYVbLX9ZpMbpKbFbMJjs5PnXYRRUFOerTqumd24ScToNtRYHh8rro37pRb0lAs5Xd4yIIZDYAbdrNt3HSJLkMGYGS5LExoIqAIYFQXxVqVTcdWF3pry3kQ/WFXDDsI5Y7C7UKmifGgeu4J10KLEDZac4Xx1OFzuOK+JrYM7Xw+X1Xrf5Hq4+zPNrn2fB1gWY7PIJSYekDtw/6n6mDJlCSmzoP38lSeLpb/aQjJEP2r1P7prV8i96TYCJL0N8FHwYCQQCgSAqMNvk+VVT5xrC+eo9HvE1pvXYAXMbFV8bO18Vkbmtiq81ZjuTF/5Keb2N3DiJl/8wsNk8VyWOKyrF1+I6z/+3Fhm4dnCHCI6mGSQJNi6A7x6S+waSO8B1b/vdN7D00FKmfD2FwppCAKYMmkpW+aW8viyZbcfWAaBWwZX9c7nrwu5C+xCcMQjxFTl2AKA4JOKrPNkJxPkKcunWxoJqUboVJBrE15Zfl5Q4HSW1lrA21reEJ/NVrUanUTMwL4V1h6vYVFAd/eJrBGMHqgKIHahuA7EDxw1mSmutaNUqBnRMDco+L+mdRc+sRA6U1fOPb/cC8ioBnUaNPYjia3YzztcDZfWY7U4SY7R0a5fo177z0uPRa9VYHS6OVZvonNG8m2D9sfXMXTuXz/d8jkuS/84G5Qxidv5sfnvub9FrgpsH3hLf7SzBXvgrS2JeomNdOah1cNlTMPIuuWFAIBAIBAI3SuxAfBPiqyJG2YXztUXsTpdHUPXG+aoU97Y1KhplvioXpNti7IDV4eTO9zdyoKye7KQY7uxpbDGWTyndOlQefefRexo5X7e6i3OjCkstfH0v7PpCvn3O5XDta34ZAWosNcxeOpu3t7wNQJeUntza62VW7dKztMII1KDXqrlhaEemjunW4rxdIGiLCPEVaJ+qiK/moO63cfuoP2UxjVGWIBwRpVtBwWr3Los3JV5xL/ov3gUTu8f5Kk+YhnZO84ivvx/RKZJDaxFJkjzia0uT2mCjxA7UWhw4nK7TluN5g8HP2IFwiq9K3uu57ZMDdtkrqNUq7rywO3M+2cay3aUAdEwLfhuu4nw12pzUWx2eQrZt7gnogI4pfkdqaNQqurVLYG9JHQfL6k+bxDldTr7e/zVz18zll6JfPD+/vMflzMmfw8VdLw578YHN7uTQ18/yif5d9ConpHaGGxZCh6FhHYdAIBAI2gZKv0RT3/96jfwdJpyvLaPMUQESWxJftW23cEuSJI/ztV1SjGc+XlFvw2h1hNUcEQiSJPHAp9tZd7iKxBgtb/5pCEe2/NTifborK6HK6pEkKWpKrYxWBwWVDeL37hO12ByuZh28YefEFvikUd/AuMflvgE/nr9vD3zL1MVTOVZ7DJUUx+Xt/05FeX8WrrIBduI0EreO7sZtF3Qn031uIBCcabSNT9kQk5MsCwrBjh2wOyVPQHSg4mvnDDkUXThfg4PifG3tdQl3aVJr2D2Zr/KX8lD3EvNoL92y2F2ehkp5chee1t3GOb01ZjsZib5/mTc4X33MfI3Te44bajxlW52Duxz9moHtmbd0n2dVQF56cMu2QH4/JMZoqbc6KKu1kOh2J2w7ZgBgYID5Tj2zk9hbUseBsnou6ZMNgMlu4t2t7/L8uuc5UHUAAJ1ax00DbmJW/iz6ZfUL6Jh+Y6qiZMGtzLCtAhU4el2N9tqXIS41MuMRCAQCQdRjaqFfQjhfvUOJHIjTaTxRDU2hCNxtUXyttTg82b8ZCXpidRpS43UYTHaKqk30zglu6XSomLd0P19uPYFGreLVG4fQJzeJI1tavk/njHjUKrlAubzO6ukbiDT7SuXIgcykGOxOFwaTnb0ltUFbxeY3kgQb3oClj7j7BjrB9Qv86huoNlcz8/uZvLvtXdRSKl209xFnu5TdhwFsZCfHMPm8zqRV7WbSpT3R6SLfsSIQhAohvtLgfD1RYw7q1bDGeUABxw64HVtHK8O3NKSs1kKtxeHJTTxTkCTJh8xXt/M1TKVJraFMnvXuieFgdxHR4XIjVUabz7mk4aKxoyBep8HpdLSwdfDQatQkx2qptTioNtl8Fl9dLskjnvodOxCG906D+Bp43mtj9Fo1d1zQjacW7wYgLy344ivI7td6q4PSWivd3OLrlkIDAAMDnID2cO/vYFk9ZcYyXtnwCq/8+gqV5koAUmNTmTZsGveMuIfcpNyAjhUQhetxfTKZTnXHsUpatvd7gOHX/1nEDAgEAoGgRcwtxA4oQqJVOF9bxJuyLYAYnSK+tr3ns9IdOZAUo/WYTzqlx2Mw1VBY2TbE1482FPLyjwcBeOY3/RlzTiZ2e+vz7Bithk7p8RytNHGwvD5qxFcl77VPbjIqYNX+crYVGSIrvpqrYdEM2LtYvt37KrlvIK75cwybw0WN2U6N2YbBZKfGbMdgsvNLwRY+2fkNRmscmdJDJDIKl0WDCeiWmcBdY7ozcXB71JKLJUt2h+fxCQQRRIivNGQOWuzyB4evy4ubQ1narlGr0GkCO4FWYgeqjDbqLPYWc22CxR/eXEdRtZn1D13iKS46E2jc+Nqa+KoIaLVR4nxVCre07vdTWoKe7pkJHCo3srmgmnF9syM5vGZRxNfEGC1qtQpnGA0D6Ql6t/jq+2tYa7F7HLvRGjtgtDrYUyznRQVbfAX4/fA8/r38ADVmO50ygh87AJCVHMPhCiNldbLD1mRzsN/tBhjcKTWgfffMlsXXZft28PK+kVid8slH19SuzBw1k8mDJ5Ooj+AFJpcL1vwblj+JWnJyxJXNs8kP8tKkW4XwKhAIBIJWMXliB04/rRPOV+/wNhor1v18tsXCrYpGZVsKeenxbD9W0yZKt4qqTPzty50A3HtJT347PM+n+3fPTORopYlD5UbO694uFEP0GWX+3ic3iRithlX7y9lSZOBP/vVYBc6xTfDprWAodPcN/B1G3umZj9ocLl5cvp8thYZGIqsNo625vwc1Gq5GkfVdyPP6uy7szqV9sj2xYvY2eDFDIPAHIb4iLz1PT9BTZbRRXGMJmvjqyXvVqgN20ybEaInVqbHY5SUJ4RBfi6rM2JwuimssZ5T42vjqf2uFW6nx0eN8lSTJIxw3XhI1tHMah8qNbCqMXvHV6CnbCk4eqS+kxuuh0kS1H6VbimCboNf4nL8ULvF1a5EBlwQdUuM85YHBJCFGy7wbBrJkRzHjz80J+v4BspKU0i1ZGN15vBaXBDnJsZ6LY74iSRKrC1bzwsa3gd9RXR+DNdbKiI4jmJM/h9/0+Q1adYS/Ao0V8MVdcHAZAItd5/Gg7TZeuvpCv/KJBQKBQHD2YfbEDpz+vaHMF0Xma8s0OF9bPr+K1bXd2IHKRmVbCp3ccVJtoXTrnTVHcbgk8rtlMHNcT5/v3z0rkeV7yzhUVh+C0fnHXnfZVp+cZJLjTu48CCuSBGtfgR8eA5cD0rrA9Quhw5CTNpu3dB+vrz7c5C5UKkiO1aHV2ig3H8Hqqsalqmdgbg8u7TGajIQ4BuWlMrRzWtRk7goE4UaIr25yU2Ld4quZPrnBWXbhmQwFqQAnMUaHxW49aQl3qHC6GoS+cBwvnCgNpSoVrTqSoynzVckPhpPHPbRzGh9vPOZZeh6NNHa+hpu0AAR0Je/VnwsyynvHbHdidThbFfr9JVSRA40Z1zc7pMJ+drJ8IqA4X5WJ58C8FJ/35XA5+Gz3Z8xdO5eNJzaCpKUT16Mmni9/u4pr+lwQHZO+gjXw6W1QVwzaWD5Mn87DhUM4v0cmY8/JjPToBAKBQNBGMNvkOVZ8i87X8GTtt1W8db4qMXKWNihmV7jF15Ocr+44qWh3vtZZ7Pzv1yIApl7Yza95XPdMeRXpofLoEF8lSfLEDvTOTSLTLYofKjdSa7GTHAajFQCmKvjybtj/rXy770S45iWIPXkOvnJfmUd4feDy3vRtn0xqnI7UeB2pcXosrmru/e4ePt71Meigb2ZfFlyzgJEdR4bncQgEbQAhvrrJTYll14laT7FMMFAymAIt21JIitVSUR8e8bXxFXLjmSa+OuTXJcYLR3KKW3QzmH13TQabxhPnU52vIAtWdqerxaKASFFviaT4Kr+GVSbfX0ODUraV4PsEKClWi0olX0yuMdvJSmq74muoUZyvpW7n61Y/yrbqrHUs2LKA59c9T0FNAQCx2lhuHXgrO3fHUlRlJ03bJ/LCq8sFP8+DH58GyQUZPdlzwb95+L/VqFTw8JVRMEaBQCAQtBkaYgeaKNwSzlevUJyvrQleyjmdtQ06X5XYgSadr9XmiIzJWz7ddIx6q4NumQlc2NO/C9Td3R0Ah8ujo7z6WLWZOqsDnUZF98xEdBo1eelxFFWZ2XGshtE9whCNULheNgLUHgNNDFz+NAy7/bTYq7JaC7M/3gbAzfmdmTa2u+d3kiTxye5PmL5kOhWmCjQqDQ+MfoBHL3yUGK3vRccCwZmMEF/dKMt1S4Ioviph7IGWbSkowpUiZIWSxstp6s4w8VV5XbxxIqZ6nK+Rfw7sroaJc2OBtVu7RFLidNSY7ew+URtwO3woMNqU2IEIiK/uyIxqP8TXaqNStuW781WtVpEcK78utWa7R2AMJi6XxObCM0B8bcb5OsiLwoHjtcd5acNLzN84nxprDQCZ8ZlMHz6du4ffTWZCJndWb6SoqpSDZfWMiaSrtL4MPp8Kh3+Ubw/4PdKEufxtwQ4Arh/Skb7to7/wQiAQCATRQ0PsQBPiq8h89Yo6L00Csbq2nPmqOF+bjh1wuSRPBmc04XRJvLPmKAC3je7q9xgV8fW4wYzJ5mjSKR5O9pbIrtceWUme87qBHVMpqjKztcgQWvHV5YI1L8Lyp0ByQnp3uOEdyB3QxKYSMz/eSqXRRu+cJB6+so/nd6X1pdy95G4+3/M5AP2z+rNw4kKGth8aurELBG0YIb66yU2Ri2ROGIIpvgbX+apMCMIhhlocDZOKcIi94aSx87U1Ghrro8D56mgsvjZMPNRqFUM6pfLjvnI2FVRHpfjq7aQ2FHhiB4z+xw74I74CHlE8VLEVB8rqqbM4iNdr6J2TFJJjhAMl17Ws1kpFvZVj1WZUKujXsfnYge2l25m3dh4f7fgIu0t+fs/JOIfZ+bP504A/EadrKAfrmZXE97tKORDJnK/Dq+DzKVBfCto4mDAPBt/I9zuL2VhQTaxOzezLekVufAKBQCBokygr7eKbcL4qoo5VOF9bpM7bwq02nfkqz2kzG8UO5KbGolGrsDpclNdb/c7ZDyUr9pZRUGkiJU7HpCEd/N5PWoLe0/FyuNxIvw6+R1sFk71K2Vaj+fugvFQWby9mayhzX0/pG6Df9XD1CxDT9HnEa6sO8cvBSuJ0Gl7+4xBidRokSeKjnR9xz7f3UGWuQqvW8vD5D/PXMX9FrzlzemIEgmAjxFc3uYrztTZ4yy5auhLtD4mx4XS+nsmxA27naxPFBKeiFG5FQ+arw535qlWrTluWPKxLuiy+FlZzG10jMbwWMUYw8zU1gNiBBvHVv9ylUGcGK5EDgzultumCpqwkxflq9bheu2cmnrb8T5Ikfjj8A3PXzmXpoaWen4/pPIbZ+bO56pyrUKtOfx56ZMluh4iULLicsOpZWPVPQILMPrK7IKs3NoeLf3y7F4CpF3QLSWGaQCAQCM5svIkdEM7XlvG9cKvtPZ9NOV91GjXtU2MpqjJTWGWKSvH17Z/lnNE/jOgUsFu1e2YCVUYbh8rrIy++ljTkvSoMchtothYZkCQp+DFUR3+Bz2739A1wxbMw5ObTYgYUNhVU8dyy/QA8MfFcemQlUlxXzF3f3MVX+76Sx5wziIUTFzIoZ1BwxxqluFwuDAaDT/dJTU0NyVgEbQ8hvrpRnK/FQXS+ejJfg1S4pVyNrbeGXgi0Os7c2AGrD7EDinhmtDkjnqeq5HVpmygJG9JJXnK+OUpLtxTxNRKxA+nu2AGDX+Kr/LfmT+GWfL/Qiq8bC6oAGNqp7UYOAGS5J/v1Vge/HKwEGiagADanjf/u/C/z1s5je+l2ANQqNdf3vZ7Z+bMZ0WFEi/tXxNcDZXUhGH0L1JXAZ3fA0Z/k24Nvgiv+BXp5md9/1hVwtNJEu8QYpl7YvYUdCQSB88wzz/D555+zd+9e4uLiOO+88/jnP/9Jr14NjuuxY8eyatWqk+535513Mn/+fM/twsJCpk2bxo8//khiYiK33HILzzzzDFptw+f7ypUrmTVrFrt27SIvL49HHnmEW2+9NeSPUSA4G1HMHvFNxg7Ic0abEF9bpN7irfNVPg9oi85XRXxtnPkKcvRAUZWZwkoTw7ukR2JozbLrRA3rDlehUau4Ob9zwPvrnpnIr0erORQFua97FOdro6Lvc9unoFGrKK+zUlJr8egTAeNywk/PwUp330C7c2QjQPa5zd6lxmTn3o+24nRJTBzUnuuHdODdre9y//f3Y7AY0Kl1/G3M33jw/AfRacJUDhYFGAwGnlu8hdgE71YcWox1zLpqcIhHJWgrCPHVjeJ8La6xBO1Kk7J0P84Lh6U3JCmxA8L5GhCKsBzrxeuSFKs7qTTp1AlLOFGcr00JwAPz5C/r4hoLJwxm2qcG6cs6SCgCfmIrk9pQoAigipDqC4YAna/JbvHe4MexvUER24e04bxXkB3RCXoNRpuTZXtKALlsy2Ax8PrG1/n3hn9zou4EAAm6BO4Ycgf3jbyPrmneuby7ZyaiUsnvgcp660muj5BxcLmc72qqAF0CXPU8DPyd59c1Jjv/XnEAgNmXnRMRV7jg7GLVqlVMnz6d4cOH43A4ePjhh7nsssvYvXs3CQkJnu2mTJnCk08+6bkdHx/v+b/T6WTChAnk5OSwZs0aiouLufnmm9HpdDz99NMAHDlyhAkTJnDXXXfxwQcfsHz5cu644w5yc3MZP358+B6wQHCWYG7R+Sr/zC5iB1qkzm1s8TZ2wOpwRW1GanMosQMZiScbCjqlx/MLlRRWmSIxrBZZ+MtRAK7olxOUcxsl9/VQeQRjqJD/Zo9UygJw75wG8TVOr6FXdhK7i2vZWmggt38Qzufqy+TYq8Mr5dsD/wgT5oI+odm7SJLEg59v57jBTOeMeO6+JJ2r/3s1Sw4sAWBo7lAWTlxI/+z+gY+vDRKbkERCcmqkhyFog4izPTfKck+z3Umt2UGKn2JLYzzO1yDHDoRHfD2TM1+9d75q1CqSYrTUWhwYTJEVX5UlY02Jr/F6LX1zk9lxvIZNBdVRJ75GMnZAyWutNgZQuJXgf+YrhMb5WlFv5WilCZUKBrdx5yvIua+HK4wUVcnRL8uL3ubuH5+n3iZPkHMTc7lv5H1MHTqVtDjfHm+cXkPHNLlB9kBZfWjFV6dDdhb89BwgQXY/2V3QrudJm72y8iAGk51zshO5YWjH0I1HIHDz3XffnXT7nXfeISsri02bNjFmzBjPz+Pj48nJyWlyH0uXLmX37t388MMPZGdnM2jQIJ566ikeeOABHn/8cfR6PfPnz6dr167MmzcPgD59+vDzzz/z/PPPC/FVIAgBJnepaVwTS7J1buer3SmFdUxtDV9jB0A+n2hK8I5GLHanxwhx6rlMXqPSrWiivM7KV1vlC++3nR+cSLXuWbLgGJEYqkbsL61DkqBdop7MpJNfj0GdUmXx9ZiBK/rnBnagxn0Duni5b2DQH1u92wfrC/l2Zwk6jYpxgwsZ8fa11Fpr0Wv0PDH2CeacNwetWshIAoGvtN2QwCATq9N4liefqAlO7qsl2JmvMfKEoD4MTtTGwfzhOF44aRBfvXv7K0vOI537qsQO6JqIHYCGtvtNURg9YLTKfwuREF89sQNmO5Lk28mHkvnqb+xAKMVX5XU+JyvJc5y2TOPJp4SNd3c9Q72tnn5Z/Xhn4jscvf8oD5z/gM/Cq0IPt9vhYCgn3DXH4d2r4ad5gARDJ8MdP5wmvBZVmXjH7eZ46Mo+bTqvVxB56urqqK2t9fyzWq1e3a+mpgaA9PSTl5l+8MEHtGvXjn79+vHQQw9hMjWckK9du5b+/fuTnZ3t+dn48eOpra1l165dnm3GjRt30j7Hjx/P2rVr/Xp8AoGgZczu1WpNxg64v19sTpfPc6CzCUV8TW7N+dro3KEtRQ9Uug0Ieo36tMfYyS2+Rpvz9YP1BdicLgZ3SvXEqwWK4nw9UmHE6Yrc30NTkQMKgzqmAng6EPzC5YQfn4b3JsrCa2YfmPKjV8Lr3pJanly8G4DUzNU8+sut1FprGdlhJFvu3MKD5z8ohFeBwE/EX04jcpJjqTLaKKmxNPlh6CtKBlOwna/hKdxq5Hw908RX92PzVnxtENB8d04Gk4bCrabHPaRzGu+sOcrmwugTX+simPmqxA44XRK1FodPQqUSF+Bv7EBqCMXXMyVywCW5+Gb/N+ys3Av0BcCmOsyl3S9iznlzuLTbpUGJgemZncSP+8oDEl+Lqkzc89EW0hP0jOnZjjHnZNK1XYI8vv1L4Ys7wVwF+iS45kXod12T+3n2+33YnC7O79GOsedk+j0egQCgb9++J91+7LHHePzxx1u8j8vl4v7772f06NH069fP8/M//vGPdO7cmfbt27N9+3YeeOAB9u3bx+effw5ASUnJScIr4LldUlLS4ja1tbWYzWbi4qJrZYZA0NYxe5yvp59v6BrNde1OyZMBKzgZ5VynNeerVqNGp1Fhd0qeeLm2QEWdUralP21OFY3iq9Xh5D/rCgC4bXTwioQ7psWj16ixOlycMJg9rt9w4ynbyjk9N3Sgu/Ngx7EanC4Jja/RFrXFsttV6RsYcjNc/k9P30BLmGwOZny4BZvDhU27hY2GZ4nVxfLURU8xc9RMNOq24fQWCKIVIb42Ijcllt3FtRTXBKd0S8lNDdaSFCXzNRxi6BktvvoQOwChL03yFiV2QN+MaKw4X3edqMVkcwTcCBpMGmIHwv+lHaPVEK/XYLI5qTbafBJfqz2ZrwE6X0OQ+brRLb4Oa6Piq8Vh4f1t7zNv7Tz2Ve4jzX47yW7x9bqBw3j597ODerxglG69tOIAW91OhBV7ywDonKrjqaQvGFP+obxR7kC4fiFkNF2gtaWwmq+3nUClgoev7BP8JlvBWcfu3bvp0KGD53ZMTOuxGtOnT2fnzp38/PPPJ/186tSpnv/379+f3NxcLrnkEg4dOkT37qIUTiCIRkwtZr42zBltTlezc8iznTqrd4VbALFaDXanwxMv1xaoNDaIr6eiiK9ldVbMNmdURCl8tfUEFfU2clNiubxf0zE4/qBRq+jaLoF9pXUcLK+PmPiqOF8b570q9MhK9PQgHCyrp1cTAm2zNO4b0CfCVS/AgBu8vvufP13PwbJ6HFRSqp3L6E7nsWDiAs7JOMf7MQgEgmYR38CNyE1VSreCEzvgcb56KfK1hrJkuy7csQNnauarl0VooS5N8hZFfNU2cwW0fUosOcmxOF0S24/VhHNoraK8h5TojHDjyX01ee9eNtucnvdKqp/O11DFDlgdTna4X+OhbUx8rTBV8OSqJ+n0fCemLp7Kvsp9pMSkcEGXAZ5txvXqEfTjKuKrv87XsjoLX25xZ4+N7kp+tww6aSp5zvSwR3h91zmeP7ie5KWtLrYVGXCdsqRNkiT+75s9AFw/pCN92we+wkIgSEpKIjk52fOvNfF1xowZLF68mB9//JGOHVvOGx45ciQABw8eBCAnJ4fS0tKTtlFuKzmxzW2TnJwsXK8CQQhQRMD4VsRXUbrVNC6pIR7LG/E1xr2isXE5cbRTUSfPf5vqrkiJ03kMPseqI+9+lSSJBe5oppvzuzTZdREIkc59lSSpwfmae7qwqlGr6N8xBfAhesDpgB+egP9MkoXX7P4wdZXXwqtLcjHj84V8s92AhIu6uJd57vInWHXrKiG8CgRBJHqscVFAbop8UhA056vnSnRwvjQaYgdCLwJaz2Dnq8XH2IFQLh33BaUsoblJiEqlYmjnNL7ZUcymgmpGdcsI5/BapN4TOxCZq+lpCTqOG8w+CeiKUKtVq/zOqg2V+LrzeC02p4uMBD2dMyJz1d5X9lfu5/m1z/PutncxO+QLXJ1SOjFz1ExuH3w7K/bUct/BrQAMci+5CiaK+Fpaa6XWYie5laWFp/L+2obssUev7gt7lyB9+TdUFgNmTSLP6GbwnmEAFBhZW7Cfecv2kxav4/yemYzp2Y4Lz8lkc2E1GwuqidWpmX1Zr6A/RoGgJSRJ4p577uGLL75g5cqVdO3a+lLOrVu3ApCbK5d+5Ofn83//93+UlZWRlZUFwLJly0hOTvbEH+Tn57NkyZKT9rNs2TLy8/OD+GgEAoGCuYWOCbVahVatwuGSsDnbjlgYTiyNDKyJ3jhf3eaNNhU7oDhfE04XX1UqFXnp8ewurqWo2kTPbB+cliFg3eEq9hTXEqtT84cReUHfv5L7eqjcGPR9e0NxjYUasx2tWuWZm57KwLxU1h2uYusxA78d3spzUHMcPrsdCt256sNug/HPgC7Wq/EcrDrIzZ/O4tjhm1ADKRnrWH77h/RID74RQiA42xHiayNyU+QPqZIgia8tTYb8ITGssQNnQ+GWd69LSpQ4Xx3uSbOuBdF4iFt83RxlpVtGm+J8jcxHjj/O1yp3OUFawun5WN6SHCLxdVNBFSC7XqN52bokSawpWsPctXNZtHcREvIFhKG5Q5lz3hyu73u9J7Q/O1l+vlPidCERlJNjdWQnx1Baa+VgWb1P5Q1mW0P22NTRHeG7h2Ddq6gA2g8h7oaFPJnWhSlVJlbtL2f1/nLWHKqk2mTn620n+Hqb7JhVlntOvaAbOSneTYoFgmAxffp0PvzwQxYtWkRSUpInozUlJYW4uDgOHTrEhx9+yJVXXklGRgbbt29n5syZjBkzhgEDZGf6ZZddRt++ffnTn/7Es88+S0lJCY888gjTp0/3OG7vuusuXn75Zf7yl79w2223sWLFCj7++GO++eabiD12geBMRZKkhvONZpaL6zRqHC6np7hVcDKK+KrXqr06N4jzOF/bkPiqOF+Tmo7R6uQWXwsrI+98XfDLEQCuG9LR78LblmgQXyPjfN1bUusZR3PvN6V0a2uhoeWdndY38G/oN8mrcThdTl7a8BIP//AoKcbHiSGBDhkWfpz5BHqtkIgEglAg/rIaoZwMnwhS7IAlyIVbSREq3DJaHUiSFNUijy9YHT46X91Lzmsj7nx1i68tBK8rS9A3FVZHzWsmSVJD7IAXjoJQoIiviqDqDYGWbUHDe8cQdPFVFtejNXLA6XLyxd4vmLtmLuuPr/f8/KpzrmJO/hzGdB5z2ntzaOc0rh/akRFd00P2vu2ZlSSLr6W+ia+fbT5GtcnOiNRaLl9/K5zYLP9i1HQY9zho5fdXXno8N43qzE2jOmN3uthSaGD1/nJWHyhnx/EabA4XmUkxTL1QZGcKws9rr70GwNixY0/6+cKFC7n11lvR6/X88MMPvPDCCxiNRvLy8rjuuut45JFHPNtqNBoWL17MtGnTyM/PJyEhgVtuuYUnn3zSs03Xrl355ptvmDlzJi+++CIdO3bkrbfeYvz48WF5nALB2YTF7kJyJ9w0l/Wv06gw2xHO12Ywu0+rkr2coyrnddY2FDugZL62a8L5CtApQyndCs45sL8UVBr5YY8cWzM5iEVbjVHE18MREl/3FDcfOaCglG7tK61rOofXaYflT8Kaf8u3cwfCDe9AejevxrCvYh+3fXUba4rWkGqfTIzUi8QYNf+74wohvAoEIUT8dTVCiR0oqbEERbgyB1l8VVyDRpvTv/ZDH2ic+epwSVgdrqA9jkijTJa8zXz1OF8jLr62HDsA0Dc3mRitGoPJzuEKo2eCEUmsDhcOd/ZlQsScr767lxWXbCBX3ZX3js3hwmJ3BuVvSJIkNhUYgOgTX+tt9SzcspDn1z3PEYPsXIjRxHDzwJuZOWomfTL7NHtfnUbN3BsGhnR8PbIS+flgBQd9mHC7XBILfj7C5eoNvOh4C9WJeohNhWtfg95XNns/nUbNiK7pjOiazpzxvagy2vj1aBW9c5Ii5gAXnN1IktTi7/Py8li1alWr++ncufNpsQKnMnbsWLZs2eLT+AQCge+YG5klmltpp9dqAIfnIr7gZBTna5KXcURK7IC5LTlf693iazPOV6V4qrAqss7Xd9YcRZJgbK/MZpfkB0q3TDnztaLeRo3JTkoAJgt/UMq2+uQ2n/ufmxJLVlIMZXVWdp2oYViX9IZfGgrh09vg2K/y7RF3wmVPgbb1sk2ny8lza5/j0ZWPYnFYSFeNJslxHQBzbxhEx7S2EWUmELRVxBlgI5TYAZPNSa3ZEfCHsdkt8gUtdqDRFVmjzeFzZqEvnLqUps7iOHPEV59jB+SJSuQzX92FW5rmRXe9Vs3AjqlsOFrFpoLqqBBfjY1iKxKacWWEmlQ/YgcM7m0Dcb4mxmjRqFU4XRI1ZntQ/oYKq0xU1FvRa9T065AS8P6CQXFdMS9veJnXNr5GtUV25WbEZXD38LuZPnw62YnZER6hjDKRP1Ba5/V9ftxVxC2Gl7lFvwwcQMcRcP0CSPUthyw9Qc/4c4PX2CsQCAQCgckd66TXqps1Zejd80YRO9A0Zqf8/HhTtgUNppq2FDtQWd984RbIsQMARREUX2stdj7+tQiQi01DRUKMltyUWIprLByq8G0lVDDwlG3lNO98ValUDMxLZdnuUrYWGRrE173fwJd3g8UAsSkw8RXoc7VXx91dvpvJiyaz4fgGAC7udC2VRXdiwMmfRnXm8n65AT0ugUDQOsGtD2zjxOo0HqGluDbwZRcNhVvBES1jtBpPZmBdiKMHTg2RN55Bua9K7ECsr85XH4S7UOBwO1/1rbR+DnG7IaMl91XJDI7Xa0Lq1m4J5e/aF/G12hM74L/zVaVSeZaxBUu8VyIH+nVIjvgFkV3lu7ht0W10ebELT//8NNWWanqk9+DVK1+lcGYhT170ZNQIr9AgvnrtfK08RNdF13KLdpl8e/R9MHmJz8KrQCAQCAShwOw+14hv4VxDOXcQztemUU6pfBdf287zqThfmyrcggbxtbDK1OoqiVDx8a9FGG1OemQlckHPdiE9lif3tSy80QMWu9MTd9CS8xUayme3FhnAYYNvH4T//lEWXjsMhTt/8kp4dbgcPPPTMwx+fTAbjm8gJSaFt65+mxznAxhMTnrnJPHXCc2vTBMIBMFDOF9PIScljmqTneIaC71zWv5QbA2LI7ixAwBJMVoqHbaQ576emmN0JpVu+ep8VXI7I+18tXnhfIVGua9RJr5GKnIA5NIsgGpjeGMHlPtXm+xBK2xTXteTliCFEUmSWHFkBU8eepLNWzd7fj46bzSz82dzTa9r0Kij0yXf0y2+Hqs2N52h1Zgdn+L86j66OeqpkhLhN/NJH+Sdu0AgEAgEgnCgLH2Pb+FcQ4mrsgrna5OYldiBGG9jB9qW89XpkjydB83FDnRIjUOlkt9PFfU2MpNaX8IeTJwuiXfWHAVk12uoOyu6Zybw88EKDpUbQ3qcUzlYVo9Lkk0hWa08xwPdpVtlhXthwSw44Y7yyZ8Blzzm6RtoiR2lO5i8aDKbijcBMKHnBF6/6nWKKmJ56uA6YnVqXv7j4IibOQSCswUhvp5C+5RY9hTXUmywBLwv5Wq0tw5Lb0iM1VJptFFvDa0QaDllghZqp2048WS+elm4ldKosT6SJVaewq3WnK+dUgE4UFYfkSyjU1EuFCRFUnz1K3Yg8MItgOS44Ir3ivga7mVSdqedj3d9zNy1c9lashUAtUrNb3r/htn5s8nPyw/rePwhIzGG9AQ9VUYbh8rrm45tsJvhuwdh0ztogPWu3nx7zlM8PuiysI9XIBAIBIKWMCnnGl45XyPjaIx2GjJfvXS+attW5mu1yYZLApUK0psxFOi1atqnxHHcYKawyhR28XXZ7lKOVZtJi9cxaUiHkB+vu/ti/KEwl27tbpT32tr55IC8FK5Qr+ef5jfghBni0uS+gV5XtHocu9POP37+B0+tfgq7y05qbCovXv4ifxrwJ1QqFS//sB2Aawa2p0dW8/EHAoEguAjx9RRy3LmvJTWBxw4oX8rBynyFhtKtkMcO2M/82AFvC7cU56vdKWGyOSPm4HR4UbgFssDUtV0CRyqMbC6q5qJeWeEYXrMYbVHgfPVDfK32ZL4G5nxNCaL4Wmuxs8+dVxqusq0aSw1vbn6TF9e/yLHaYwDE6+IZmzKWeTfMo3dW77CMI1j0yExkg7GKg2VNiK8VB+CTW6F0JxIqXnVO5Dn7dSy6aGRExioQCAQCQUt4EzugzBtF5mvTWBxK5qtvzldrGxFflbzXtHg92hbOIfLSZfG1qMoU9kLXBb/IJa1/HNkpLC7Mbu0iI77uLVbyXltZXWu3kLz8r7ymfwuAmnZDSLnpPa9ir7aWbGXyoskeo8Q1va5h/oT55CbJma5Wh5MlO0oAuHZQ6IVugUDQgBBfT6F9ahwAxTWBO18VATNYma/QIL6GOgbgVPH1bI4diNNp0GlU2J1yaVKkRESbx/nauvN2SKc0WXwtiLz4Wm+V30sJMZFb0pKWoGS+eu9eVjJfUwN0vgZTfN1aaECSoHNGfMhdCUU1Rby4/kXe2PQGdTZ5spidkM09I+7h9oG3s37lerqndQ/pGEJBj+xENhyt4kDZKaVb2/4Hi2eC3QgJmXzU4RH+tT2T/G4ZUVNsJhAIBAJBYxTna7yu+bmpyHxtGSV2INHrzFf5+Tx1lWC00pD32rKZoFN6POsOV1EY5tKtncdr2HCkCq1axZ9GdQnLMbtnJQBQWGnC7nS1amwJFntLZOdr79wW3KaVh2QjQInsTn3NcTXWng9zfyvCq81p4++r/84zPz+Dw+UgPS6dl654iT/0+8NJ5z2r91dQY7aTlRTDyG4ZAT8mgUDgPUJ8PYWcZNn5Gqj46nC6PMt7gul8VZbEhDzz1XE2ZL5690WrUqlIidNTUW/FYLJ7BPpwozhfW7pqrTC0cxqfbT4WFbmvyns10cssrVCguFdtDhdmu5N4fesffUrBWlork9XWSA2i+LrR/XoODWHkwObizcxbO4//7fwfTkk+I+nTrg+z82dz44AbidXGYrdHNv84EHq4SxYOKiULNhMs+TNs/Y98u8sF1F/1Gs+8tBtwMGVM6Bp3BQKBQCAIBGWVXYuxA8L52iJK7ECyl+JrXBvLfFXE13aJLV+0z0trKN0KJwt+ll2vEwbkelaghpqc5Fji9RpMNicFlSZPIWsokSSJPe7Ygb7NlW3t+BS+vg9s9RCfwQ+9n+Kfa1K58HjLDt1NJzYxedFkdpTtAOC6PtfxypWvNFl6++XW44AcORCpImSB4GxFiK+nkJuiiK+BxQ40vhoazOUT4XK+Kktp0uJ1VJvsZ5b46n5s3jpfAVLitFTUWyNauqU4FvReiq8gN2Q6nC6vBNtQoURWJEbQ+Rqv16DXqLE5XVQZbV6Jr0o5QaCZrx7nqw+RB82xWcl7DfJyMJfk4ruD3zF3zVx+PPqj5+cXd72Y2fmzubzH5ahVkXsPBZOe2fIE+0BZPZTtkd0F5XsBFYx9EMb8mf/+UkCd1UH3zATGnhNZ57hAIBAIBM1hdkc7tVS4pThfbcL52iRm9ymOt5mvMe7nWol8iHYq3LEDGYmtOF8zZPG1KIzia1mtha+3nwBg8ujwXexWqVR0z0xkx/EaDpXXh0V8LauzUm2yo1Zx+vEa9Q0A0Hk0XPcWWbXxsOYXth0zNLlyz+qw8sSqJ3j2l2dxSk7axbfj1Stf5YZzb2hyDPVWBz/sLgVgoogcEAjCjhBfTyG3UexAIOVKjb+QvXVYeoOyJCb0ma/yBC0jMUYWX8+kwi3F+epDEZrceG+kxhy4gOYvdpf3sQM9sxJJitFSZ3Wwt6QuosumFeHe2+VcoUClUpGWoKO0VnYvd2xFu3Q4XZ6/sWjJfHW6JLYUyuLrsC7BEV8tDgsfbP+A59Y9x+7y3QBoVBp+1+93zM6fzZDcIUE5TjQhT3glhlUvQXrjPVQOMyRmw3VvQdcxOJwuFv5yFIDbz++GWrgCBAKBQBClmLzKfJW/x4TztWksTv8yX9ta7ECrztf08Iuv/1lXgN0pMbRzGoPyUsN2XIDumQke8TUcKK7XbpmJJxuzyvfLRoCyXYAKxsyBCx8EjZbe8S70GjUGk52CShNd2iV47rb+2HomL5rMnoo9APzu3N/x0hUvkZmQ2ewYvt9ZgtXholu7BPp1aCV3ViAQBB0hvp6CEjtgsjmptTg8womvWBqVbfkr4DaFsnQ75M5XdylVRoKeg2E4XjhpcL56L74GM7fTX+wO72MH1GoVgzunsXp/OZsLq6NCfI1k4RbIImpprdWr0i1Do9fZ38+AU+8f6Htnb0ktRpuTpBgtPQNsJq00VTJ/43xe2vASpUb5CniSPompQ6dy78h76ZTSKaD9RzM5sQ5eipnP1aqfwAF0uwgmvQmJ8mT1250lHDeYyUjQh6VxVyAQCAQCf/EqdsC90ktkvjaNkvnqrfPVk/naRmIHKj3ia+uZrwDFtRasDqdPKwT9wWJ38p/1hQDcfn74I566u2OoDpUZw3K8vSVK2VajOfy2/8LiWe6+gSyY9AZ0v8jza71WTd/2yWwtMrDtmIEu7RIw2808tvIx5q2dh0tykZ2QzasTXmVSn0mtjmHRNtllPHFQh6DqEwKBwDuE+HoKcXoNqfE6DCY7JTWWwMXXIJZtQfgyXxXnazt3qc8ZJb76WLgFDbmdBlPkxFeHx/nqnWg8tJMsvm4qqObm/C4hHFnLeGIHvFjqH0qU4iwlTqAllLzX5FhtwJENyUESX5XIgUGdUv3OaDpUdYjn1z3Pwq0LMdllZ0PH5I7cP/J+7hhyBymxZ3ixVMlOVJ/cytWqAzglFQf73Uev6x4DtfwaS5LEWz8dBuCmUZ3D0rgrEAgEAoG/mD2FW8L56i8WT+yAd+d8bS/zVZ7TtuZ8zUjQe3JQj1eb6ZYZ2qX4X209QZXRRofUOC7re3o2aajp7l76H27na5/cZLAZYclfGvoGuo6BSW9B0unPw6C8VLYWGdhaZCAzo4DJiyazv3I/ADcNuIkXxr9ARnzrxVnldVZ+OVgBwMRB7YP0qAQCgS8I8bUJclPiMJjsnKgx0yvHP4eZ50p0ECMHoJH4GmIx1OJ2vrZzlw2dkbEDPrw2wRLQAkFxLOi8FN6U3NdIl27VRUHsAEC6+73sjYBe7d4m0LItaBB9DQG+d5TXcVjndJ/vu7ZoLfPWzuPzPZ8jITuoB+UMYk7+HH577m/RaSJXhhYWJEnO0fr2AXBaMWgzmWKcxvlp19BL3fA5sLGgmm3HatBr1fwpv3PkxisQCAQCgRd4EzugzHeF87VpLD47X+Xn2mpvG8+n4nzNaEV8ValUdEqPZ29JHYVVppCKr5IkseAXuWjrlvM6R6SbwuN8La8PKGrQW/YWy87XYfEl8OaNct+ASi1HDIyZA+qm/4aVOIZFO7byxOY/ISGRm5jL61e9ztW9rvb6+N9sP4HTJTEwL/Wk+AKBQBA+hPjaBLkpsewprqWkxuL3PpQr0S0tA/IHpXCr1hJaEVC5mqt8URttZ5L46n5tfHC1BUtACwS7UxbNdF6KxoM6paJWwbFqM6W1FrKTw9MgeirGKIkdSHVnt3oTO1DtdsemBpj3Cg2xA7UBvnc2usXXoV6WbTldTr7a9xVz185lTdEaz8+v6HEFc86bw0VdLjo7lhxZamHx/bDzM/l2j0tZlP0gvy4vJecUt8Obq2XX63VDOrTqEBEIBAKBINKYPSvtmp9jKSumhPP1dFwuyQ/xVX4+zW3O+dr6nDbPLb6GOvd1zaFK9pbUEa/X8LthkYm66pwRj1ol96iU11vJSgrdeZLV4eRQeR03aFYyfNn74DBDYo67b+CCFu9rUx8AoLI2HilWw62Db+K5y54jLc63/gdP5MBA4XoVCCKFEF+bIDdF/vAtDkR8bZT5GkwU8TWUzldJkjzuUKUZM9QFX+HC6ZI8Imaby3x1Oxa0XjpfE2O09M5JZndxLZsLqrmif24oh9csntiBiGe+eh8doWyj3CcQGr93/L2yXlpr4Vi1GbVKFtVbwmQ38c7Wd3h+3fMcrDoIgF6j58b+NzI7fzbnZp3r8/HbLMXb5BKDqsOg0sC4xyD/HjruKwdKOVBa59n0SIWRZXvk/NtIZI8JBAKBQOAritkjroUSWb0ivrrnv4IGTHYnEvK8LNnbwi1t24kdkCTJ68ItaMh9LQyx+LrgZ9n1ev3QjqQEYa7tD7E6DXnp8RRUmjhUZgyp+Hr4eCn/0rzCbzS/yH0D3S+G37zh6RtoinpbPQ/98BAvb3iZjvwXDYm8Nn4Rd+Vf6fPxCyqNbCk0oFbBVQMjcz4oEAiE+NokHvHVYPZ7H0pmatDF1zBkvtqcLiT3/Ez5oj5TMl8bX/WPaWGieiqK87Umgpmviviq90E0Hto5jd3FtWyKoPiqCPeRF1/lCwneZL4q7ti0IDpf7U4Js91JvB/Zt0rea++c5Gafx9L6Ul759RVe/fVVKs2VAKTFpjFt2DRmjJhBbtJZNNmSJPj1Lfj+YXDaICUPrl8AeSMAPIVlhyuMOF0SGrWKBT8fQZLgol6Z9Aiw0EwgEAgEgnBgcq9Ma2luoayYEs7X01HmqFq1ymtThrKqUYloi2bqrY7TDDUtEQ7x9UiFkeV7ywC49bwuITuON3TPTJTF1/J68ru3npvqFyU76PjxTfTRHMWJGs0lj8DomZ6+gaZYcWQFd3x1B0cMR0AFWalGKg2JJKj8M1B8tVV2vY7u0S6kIrNAIGiZ8AestAFyUuIAKKn13/mqXA0NdmFLUows5IRSDLU0yjBSlqgYzxDx1dpooqT3IV8oNU5+HiLrfJUVcW0LX9an4sl9LYxc7qsSWRHp2IE0X2IH3CJ7ahCuxsfrNZ6yC38L21qKHNhTvocpX02h8wudeWr1U1SaK+ma2pWXrniJoplF/N8l/3d2Ca9mA3x8MyyZIwuvva6EO1d7hFeADmlxxGjV2BwuiqpMVBttfLKpCIApF3SL0MAFAoFAIPANsxcFv8p8V2S+no5iZkmK1Xq9MqnB+Rr9z2elO3IgXq/x6uJ/g/jqvwGpNd5xZ71e0jsr5KVerdE9U84+DUnpliTBxgXw5iUkGY9SLKXz7jmvwAWzmxVe66x1TFs8jUveu4QjhiN0SunE0puWcuOQ0QBsKzL4MQyJL7ceB+AaETkgEEQU4XxtgvZu5+uJAJyv5hCJr+FwvioCpUrVkHl5phRuKVd/tWqVT+HuSuGWwdy6cBcqPIVbGu+XrSti3c7jNVjszoi0txut8vvJ2yytUJGW4EvsQPCcryqVipQ4HRX1Nr7dWUKHVN+vOP90oByAYV3k11OSJFYXrGbu2rks3r/Ys93IDiOZc94cftP7N2iaCe4/ozm+CT6ZDIYCUOvg0idh1DT5w6wRGrWK7pmJ7C6u5UBZPftL67DYXfTNTQ6d80EgEAgEgiDTEDvQgvgqnK/NUudHNJaS+WqxRb/z1ZfIAZAzXwGKqkwhKaGqMdv5ZNMxAG6LgoinhtItY3B3bKmFr++DXZ8DsCV2JLcZJvNAj9HN3mXZoWXc8fUdFNYUAnDX0Lt49tJnSYpJQm2TY7G2+iG+7jpRy6FyI3qtmsv75fj+WAQCQdAQ4msT5DTKfPX3i8czGQpR4Va9zYHLJaH2Mv/TF5T2zlitxiOY1dscYWmCDDXKY/Ml7xWiI3bAoRRu+SAad0yLIzMphvI6K9uP1TCia3qohtcsinAfaedrqg+xA8o2wch8lfejp6LexlOLdwe0nwEdk/jvzv8yd81cNhVvAkCFiom9JzInfw7n5Z3X5v9G/UKSYN1rsOxRcNkhtTPcsBA6DG32Lj2yZPF194la/rO+AIApY7qenc+fQCAQCNokJvf5RrxwvvpFnbvA2BeDgGJkaAuxA0rZljeRAyCfN4C8wrLaZCc9IXATQmO+2nYCk81Jr+wkzouCi93ds9zia1kQna8ntsp9A9VHQK2FSx5j6opeVOOgT27yaZvXWGqYs3QOb215C4CuqV1565q3uLjrxZ5tBnRMlcdZXk+txe51PjHIzznAuD5ZJPlwP4FAEHyE+NoEue7YAZPNSZ3V4dMHnILyhdxSAL4/KJMDSZJD4kORo9kQmaD27F+S5Ocj0gJaoCivS4yPDlBPY73F4cmIDDc2j/PV+/eUSqVieJc0luwoYcORyrCLr1aH0zPuRD+yToNJult8NXgRO+Ap3ArSpPOeS3ryn7UFuCT/yi6ckhNt7FEu+s8ACmpkoTBWG8utA29lZv5Mzsk4JyjjbJOYqmDRdNi3RL7d5xq45iWIS23xbj3dE+6Fa45gMNnJTo5hQn+xHEsgEAgEbQeTF2YPZcWUVYivp1HXKHbAWxTx1e6UInZO4C2+Ol9jdRqyk2MorbVSVGUKuvi6xR2jdUX/nKi42K04X48bzJhtzsBMU5IEG96EpX9t1DewkPLUAZR//QMqFZyTfXKnwLcHvmXq4qkcq5XdwPeMuIenL3maRP3JcQyZSTF0SI3juMHMzmM1nNejnVdDcrokT97rxEEd/H9sAoEgKLRtJS1ExOk1pMbrMJjsFBssJOf4Ib7aQhM7EKNVo1WrcLgk6i2OEImvijtUQ5xOg1oFLkm+CtrWxVd/na+K+AryVfLUICxH9xWHH7EDACO7ZrBkRwnrj1QxIxQDawElcgAgISayy+CVCAGjzYnV4SRG2/x4glm4BXLGkj85S8drj/Pv9f/m9U2vU1NeA0BmfCYzRsxg2rBpZCY035J6VlC0AT69DWqKQKOH8U/D8DtOixloih5u8VUR2m89r6tPZXYCgUAgEEQaizeZr+75jl3EDpyGEjuQ5MP5TeOIB4s9uo0pSuZrOy+dryDnvpbWWimsMjEwLzWo49l+XJ7LDuwY3P36S3qCnrR4HdUmO4cr6jm3fYp/OzIb4KsZsOdr+XavCTDxZYhPZ687OqxrRoLn77TaXM3M72fy7rZ3Aeie1p0FExcwpvOYZg8xqFMqxw1mth4zeC2+bjhSRUmtheRYLWN7neXnDAJBFBC93xYRJic5VhZfa8z0yvG9+doTgB9k8VWlUpEYq8VgslNvtQPBbyxUMl9jdWr5eDFaai0O6q0OsoN+tPCiPDZfxVedRk2CXoPR5sRgioz4avcjdgDwuF03FVRjd7p8vn8gKEVtsTq1Txm7oSApVuu5kCA7HVsSX4NXuOUP20q2MW/tPD7a+REOl/wc9sroxez82dw04CbidHERGVfU4HLB2pdg+ZPgckBaV7jhHWg/yOtd9MxucBXE6zX8cUSn4I9TIBAIBIIQ4okd0DV/SqdctBexA6fjj/O18TmEOcrFV1+dryDnvv56tJrCKlNQx1JvdXiKrfp18FPkDAHdMxPZWFDNoXKjf+LrsU3w6a1gKJT7Bi57Ckbe5TEC7CmuBfBEDny972vuXHwnxfXFqFBx/6j7+fvFfydeF9/iYQZ1TOWb7cVsLTR4PbRF7qKtK/vntmg6ORtxuVwYDAavt09NTUXtQ+m1QNAU0fttEWHap8axt6SOkhqLX/cPVeEWyLmvBpPdM2EINorzVRm7R3w9A0q3lMItf76AUuP1GG1masyRyX21+xE7ANArO8nj5N55vIbBndJCMbwmqfejyCBUqNUq0uL1VBptVJtsZCc3feFCkqSgFm55iyRJLD20lHlr57Hs8DLPz8d0HsOc/DlMOGcCapX40sdYCV/eBQeWyrfPnQRXvwixp+dotUTnjATPKoLfDssjJUJCu0AgEAgE/uBySQ1mjxadr+7CLSG+noZybpPoQ8ScWq1Cr1Vjc7g8zuNopdLou/jaqVHpVjDZdbwGSZKLrTOTvB9PqPGIr77mvkoSrHsVlj3WYt/A3uI6ADplaLjp85v4YMcHgGyqWDBxAeflnefV4RQX8rZjBq+2tzqcLNlRDMA1g0Ss1qkYDAaeW7yF2ITWTXYWYx2zrhpMenr4u1MEZxaRV0SiFKV064Sf4qsiYAa7cAtwh2WbPcJWsFEmEkouamKsFmoI2fHCSWNXr68kx+k4bjBjiLD4qvUxdkCtVjG8SzrLdpey4UjVWSu+guxkrTTaqDY2/xrWWx04XLLLOBziq81p46MdHzFv7Tx2lO0AQK1Sc0PfG5idP5vhHYaHfAxthoI18OntUHcCNDFwxT9h6K1exQycik6jZmyvTDYXGrg9Chp3BWcGwkkhEAjChbVRjIBXhVsO/3Lnz2Tq/YgdAIj1iK/RLWhX1PlWuAUN4muwna/bj8mRA/07Ro/rFaB7VgKAx5XrFaYq+PJu2P+tfLvvRLlvIPb0x7anRBZfX9z0F4odS1Gr1MzJn8PjYx/3aSVbvw7JaNQqSmutlNRYPFpFc6zaV06txUF2cgwju0a+3CwaiU1IIiE5NdLDEJxFRIciEoXkul1xJTVmv+7vcb6GIENQmSCEyvna4A6Vx64spzkjxFd7AM5Xd+5rpJyviiDoT2zAyK6y+Lr+SBV3Xtg92ENrFuU9Ey1LsmQx1ejJdG0KJQM0RqsOycUThWpzNa9vep2XNrzEiTo5DD9Bl8CUIVO4b9R9dEntErJjtzlcLvj5OfjxaZCckNFTjhnI6RfQbt+8eRhWhyskKxQEZyfCSSEQCMKFydYwL2/pe0yZN4rCrdPxJ3YAZHNNrcUR9c7XigCcr0EXX915rwOiJO9VQSndOlRu9O4OhevlvoHaY632DZyoLWVvSTWgocy2lb7ZfVlwzQJGdhzp8zjj9VrOyU5iT3EtW4sMXJ6S0+L2i9xFW9cMbB/VpXACwdlEdCgiUUhuqnwlqthf56sX7aP+kuieIIQqBsBySmSC4lo8o2IH/HC+KqVbNS0Id6FEKUrwtXAL8Fzx/PVIVVibWY1R5nxNc7e2tiS+Brts61SOGo7ywroXeGvzWxjt8kSvfVJ77h1xL1OHTiUtLnzO5DZBfTl8PgUO/yjfHvA7mPAcxCS2fD8vUKlUQngVBB3hpPAfs9mMJEnEx8sn/wUFBXzxxRf07duXyy67LMKjEwiiCyXvNUarbnFep8QOiMKt06nzc56qzB2UFXXRSkWdIr767nw9YTAHtStih3u5fP8oynuFBvH1cHk9LpeEurm/JZcL1vxb7huQnJDeTTYC5A48bVNJkvhk9yfc89U/iJOewoWRv1xwB4+NfZQYrf+RC4PyUhrE137Ni691Fjs/7CkFYOKgDn4fTyA4U4nUfDM6FJEoJNdt5fdbfHWENvMVGiYMwcYzdvdkTbkabLSdCeKrf4Vb0FC+FLHM1wCcr33bJ5MUo6XO6mBPcW3Ygu49WVrRIr66X0PF3doUoSrb+vX4r8xdO5dPd3+KS5JPgPpn9WfOeXP4fb/fo9eEv8Qt6jmyGj67A+pLQRsHE+bCoBv9ihkQCATRz8SJE5k0aRJ33XUXBoOBkSNHotPpqKio4LnnnmPatGmRHqJAEDUoZomWIgegYd4oMl9Px1/na6x7BZ3ZFr3PqdXhpNb9+HxxvmYmxRCjVWN1uDhhMNM5IyHgsdSY7BytlJ20A6IsdqBjWhx6jfx4jxvM5KU3UXxlrIAv7oKD7k6GftfD1S9AzOmrXErrS7l7yd18vudzEhxjiQPObZ/K0+P+L+CxDuyYykcbithWZGhxu+93lWJ1uOiemcC57X3rRBAIzgYiNd8UQWPNoOSo+F24pThfQyG+htz5qrhD5bEn6EMbcxBOAincUpyvLQl3oaShcMt34UmjVjGsi+yoXH+kKqjjaonojB2AKmMLzldj8JyvLsnF1/u+5sJ3LmTEWyP4eNfHuCQXl3a7lO9v+p5td23j5oE3C+H1VFxOWPkPeG+iLLxm9oapP8Lgm4TwKhCcwWzevJkLLrgAgE8//ZTs7GwKCgp47733+Pe//x3h0QkE0YXJy3MNj/NViK+n4bf46l5BF82xA8pcV6tWkexDoZhKpQp69MDOE3LkQKf0eFLDWGbrDVqNmi7t5MfbZO5rwRqYf74svGpj5ZLX6946TXiVJIkPd3xI31f78vmez9GqtYzt8EcAhnUKTuGVUrq143gNTlfzGc6Lth4HZNerSsybBYLTiNR8U4ivzaA4X+utDmotvottZreAGQrna5IngzU0IqD1FOerR+w9ozJf/YgdiLTz1RM74N+f7Qh39MD6w5VBG1NreAq3fJzUhgqfYgcS/He+mu1m3tj0Bn1f6cs1/72G1QWr0al13DzwZrbeuZWlf1rKZd0vExOipqgrgfevhZXPgOSSBdcpP0JWn0iPTCAQhBiTyURSknxCu3TpUiZNmoRarWbUqFEUFBREeHQCQXRh8jLiTCncsonYgdOo87dwy31+Z4ni2IHGZVvNLqVvhmCLr9FatqXQZO6rywWr/wXvTIC6Yrlv4I7lTRa9FtcVc+3/ruXGz2+kylzFoJxB/DrlV9L1ciRBn9zguE/PyU4iXq+h3upotiCsvM7KLwcrADnvVSAQnE6k5ptCfG2GeL3W43T0x/2qXAkNSeZriAuwLKcIx8qExHgmiK9K7EAAma+GCMcOaP0UX0d2k0tdNhytwtXC1dJgEnWZrz7EDvjjfC03lvPEyifo/EJn7lx8J/sq95ESk8IDox/gyH1HePfadxmYc3o2lMDNoRWyu+DIatAlwG9eh4mvgL6JJWACgeCMo0ePHnz55ZcUFRXx/fffe3K3ysrKSE4WSycFgsaY7fIcK17f8hxLOF+bxxOP5bPz1S2+2qP3OVXKtjISfM8YzQu6+GoAYECU5b0qNIivbkGzvgz+MwlW/F02Agz4PUxdeVrRqyRJvLv1Xfq+2pev9n2FTq3jybFPsuGODQzKGcTe4loAeue2XsLpDRq1yhMdt7WZ6IHF20/gkmBQXipd2gUeGSEQhILjx49z0003kZGRQVxcHP3792fjxo2e30uSxKOPPkpubi5xcXGMGzeOAwcOnLSPqqoqbrzxRpKTk0lNTeX222+nvr7pixKnEqn5phBfWyCQ3FeP+BrC2IFQxQBYPYVb8tsj4Qwq3PJEKvgRO5AaJ4txEXO+BhA7AHLAfbxeg8FkZ39ZXTCH1iz1Vvm9lNDKiUG4UJY6teR8NfhRuLW/cj/TFk+j0wudeHzV45SbyumU0onnxz9P0cwi/jHuH3RIFoH3zeJ0wPKn4P1JYCyHrHPlSe7A30d6ZAKBIIw8+uijzJkzhy5dujBy5Ejy8/MB2ZUwePDgCI9OIIgulLzR1s41lHmjVThfT0KSpAbnq5+xA+Yojh3wlG0l+S++HqsyB2UsUe98zZJFykNl9XB4lWwEOPyj3Dcw8VWY9PppRa/Hao9x1UdXceuiWzFYDAzNHcqmqZv424V/Q6fRUVlvpcz9GvTKDo74CrKoCjSb+7po6wkAJg4SrldBdFJdXc3o0aPR6XR8++237N69m3nz5pGW1lA6/eyzz/Lvf/+b+fPns379ehISEhg/fjwWS4Mud+ONN7Jr1y6WLVvG4sWLWb16NVOnTvVqDJGab0aHIhKl5KbEsrekjmKD7188ZnvoC7dC5Xw9NRfVI/aeSc5Xf2IH3M7XmghkvjpdEpLbrKr30/mq06gZ2jmNnw5UsOFIFb1zQu8iirbYgXQldqClzFcvC7ckSeKXol+Yt3Yei/YuQkJ+gYbmDuXP5/2Z6/peh1YdHY87qqk5LpdqFa6Rbw+dDJc/A7q4yI5LIBCEneuvv57zzz+f4uJiBg5sWCVwySWX8Jvf/CaCIxMIog+Tuwi31dgB4XxtErPd6cnN9Dd2wBrF4mule67bLsH3lVzBjB2orLdy3H0uHa7CX1/pnpmIGheXlCyA9z4BJMjsAze8A1m9T9pWkiQWbFnArKWzqLXWotfoeWLsE8w5b85J8/69JbLRpXNGfFC7LwZ2TAVgm9tN3JijFUa2FhlQq+CqAUJ8FUQn//znP8nLy2PhwoWen3Xt2tXzf0mSeOGFF3jkkUeYOHEiAO+99x7Z2dl8+eWX/P73v2fPnj189913/PrrrwwbNgyAl156iSuvvJK5c+fSvn3L7/9IzTeF87UFclLkk39/nK9K4VasH8vbWyMp5IVbJ4898YyKHfA/81UR4wzm5oW7UNF4wuxv7ADAiC5y9MD6w+Ep3WqIHQj+RQh/UGIHqlsQ0FtzvjpcDj7Z9Qn5b+dzwcIL+HLvl0hIXHXOVay8ZSW/TvmV3/X7nRBeveHAMtldULgG9Elw3dtye6wQXgWCs5IVK1aQmprK4MGDUasbvutGjBhB7969W7inQHD2oRg94kXmq18oKwjVSK0+h6cSq1ViB6JXfA3E+RpM8XXHcdn12q1dgk/FX+Gke1w9/9E9zVTpY0CCwX+CKStOE14Lawq5/IPLuePrO6i11jKyw0i23LmFB89/8LR5/x535ECfIJtdBnVKBWBvcd1p77+vtsmu19E92pHpx+suEARCXV0dtbW1nn9Wq7XJ7b766iuGDRvGDTfcQFZWFoMHD+bNN9/0/P7IkSOUlJQwbtw4z89SUlIYOXIka9euBWDt2rWkpqZ6hFeAcePGoVarWb9+fatjjdR8U6gDLdDeEzvgm/PV5ZI8Il9IYgdi5C+u0GW+nuzaDbXTNpx4Crf8eF08ztcIxA40Fl/9jR0AGNnNXbp1pBJJkkJe+ORxvsZEx2RLiR2otdhxOF1NCtnNFW7V2+pZuGUhz697niOGIwDEaGK4eeDNzBw1kz6ZohDKa5x2WPEU/PKifDtngOwuyOge0WEJBILIcs011+BwOBg+fDhjx47lwgsvZPTo0cTFiQsyAsGpmL0t3HIbDlySvJJK42P50pmKIr7GavB5Pqw859Gc+ao4XzP8cL7mpcufuTVmOzUmu6d02B92uCMHBkRp5AAHl5Pw+VTO01RglGIoG/tPul40+aRNJEnijU1vMGfZHOpt9cRqY3nqoqeYOWomGnXTf3+K8zVYea8K7VNiaZcYQ0W9lV0nahjaOd0zxi+3Hgfg2kFnT9SZy+XCYDB4vX1qaupJYpsgePTt2/ek24899hiPP/74adsdPnyY1157jVmzZvHwww/z66+/cu+996LX67nlllsoKSkBIDs7+6T7ZWdne35XUlJCVlbWSb/XarWkp6d7tmmJSM03hfjaAjl+Zr42zlQKReFWUogzXxtyUU92vp4R4msgsQPuiYfF7sJid4YkUqI57M6GgixdAF8YA/NS0GvVVNTbOFxh9ATMhwrFnZ0QJc7XVLeALknyhDIj8fSrwtVGJXZAnqwW1xXz0oaXmL9xPtWWagAy4jKYPnw6dw+/m+zE7NP2IWgBQxF8ehsc2yDfHj4FLvs76GIjOy6BQBBxqqur2bBhA6tWrWLVqlW88MIL2Gw2hg0bxkUXXcTf//73SA9RIIgaTDbv+iV0jS402xyukJybtEXqLPJ8z59krJi2kPla73a+NjHXbY14vdYj8BVVm0iJ91843X5cyXtN9XsfIcHpgJVPw0/PARIFuq5Mrp/OtKRxdG202ZHqI9zx9R2sOLICgNF5o1kwcQHnZJzT4u73lrjLtoLsfFWpVAzKS+GHPWVsLWoQX3edqOVwuZEYrZrLzj17zk0MBgPPLd5CbELrIrfFWMesqwaTnp4ehpGdfezevZsOHRqE/5iYpj97XC4Xw4YN4+mnnwZg8ODB7Ny5k/nz53PLLbeEZayRmm8K2b8Fct2xAyU+iq+Nv4hj/Sh2ao2Gwq3QODA9AqV7MncmFW55Ygf8EE4T9VoUs0BtmN2vDrfzVaNWoQ7AsRCj1TDYHdQejugBo01xvkbHdR6tRk2y+++nuegBJXag3HyUyYsm0/mFzjzz8zNUW6rpkd6DV698lcKZhTxx0RNCePWVvUvkmIFjGyAmBX77HkyYK4RXgUAAgE6nY/To0Tz88MN8//33rFu3jj/84Q9s2LCBZ555JtLDEwiiCq9jBxoZDmwi99VDY+err7SJ2IF6t/M10XfnK0Ant/s10OiBqHS+1hyHd6+Gn+YBEgy7jXf7vs1hqT2Hyo0AuCQXr2x4hf6v9WfFkRXEaeN4fvzzrLp1VavCq8PpYn+p3LreNzf4HRue3NdGpVuL3K7XcX2ySYrSeIdQEZuQREJyaqv/vBFoBf6TlJREcnKy519z4mtubu5pLtk+ffpQWFgIQE5ODgClpaUnbVNaWur5XU5ODmVlZSf93uFwUFVV5dmmJSI134wORSRKyU31z/mqTIb0WnVAQllzJDVyooZi6bjifFWcnZ6M2TPC+ep/5qtarSIlTke1yY7BbCcrOXyCkTJZ1gbh/TSyWwbrj1Sx/kglfxzZKeD9tYQi2EdL4RZAWoKeWovDI7I2xmJ3YHQ7Sa78aAwulTxxGp03mjnnzeHqc65udnmRoAUcNvjhcVj3iny7/RC4fgGkd23xbgKB4Oxi//79rFy5kpUrV7Jq1SqsVisXXHABc+fOZezYsZEenkAQVTTEDrQ8x2o8dxS5rw0o4mucP+KrLvpjBwJxvoKc+7q50BCQ+FpWa6Gk1oJaFRoR0i/2L4Uv7gRzldw3cM2L0O86Oq85CpRwqLyeQ1WHuP2r21lVsAqAMZ3H8PY1b9MjvYdXhzhSYcTmcJGg19AxLfjLmJXc161u8dXpkjx5rxMHiaItQXQzevRo9u3bd9LP9u/fT+fOnQG5fCsnJ4fly5czaNAgAGpra1m/fj3Tpk0DID8/H4PBwKZNmxg6dCgg57i6XC5GjhzZ6hgiNd+MHkUkCslxi2v1Vgd1FrvXV5HMXi4D8hdFyHJJstAb38qky1csbudr7CmxAyabs81nRQUSOwB4xNdw57463LED+gDKthRGdU3n38jO11DnviqCfUKQ36OBkBqvp6DSRJWxQXy1O+38b9f/eHb168CDSDhBZeb6vtczO382ozqOityA2zrVR+WYgeOb5Nuj7oZxT4DWPyeGQCA4c+nduzeZmZncd999PPjgg/Tv3z/k2eQCQVvF29gBlUqFXqvG5nCd1CFwttMQOyC1suXpxLljB5RzpmjD5ZI889xAxFcIzPm63e167ZGV6FlJGTGcdlj+JKz5t3w7dyBcv9DTN6BEsW0sLKL/a2MwO8wk6BL4x7h/cPfwu1GrvD8H2+POe+2VkxQSI9aADqmA/NpUGW3sLamltNZKcqyWC3tlBv14AkEwmTlzJueddx5PP/00v/3tb9mwYQNvvPEGb7zxBiB/Z91///38/e9/p2fPnnTt2pW//e1vtG/fnmuvvRaQnbKXX345U6ZMYf78+djtdmbMmMHvf/972rdv/QJEpOab0aOIRCEJMVqSY7XUWhyU1Fi8Fl+VJSihEl/jdBrUKll8rbc4gi6+nlpK1fjL0mhzRG1TpTd4HpufcRAp8XqoNGFoZsl6qFAmy9oAyrYUBndKQ6dRUVJroajKTKeM+ID32RR2p8vjNI6W2AGAdHd2r8Fkp8ZSwxub3uDF9S9yvO44Oldn2gMxWicH7t1Pt7RukR1sW2f3V7BoBlhrIDYVrn0Nel8Z6VEJBIIo5d5772X16tU8+eSTLF68mLFjxzJ27FjOP/984uND810lELRVzHb5AndrsQMgX7y3OVzC+dqIgGIHFOerLTrFV4PZjtMli8rpfhRuAeS5xdeiQMRXJe/VLRZGjFP7BkbcCZc9BdpGwrRWXuJcVa/GHGvj4m4X89bVb9E1zfdVWnuK3XmvIXL7psTr6NYugcMVRrYdM/D9TrlgaMKAXL/PcQWCcDF8+HC++OILHnroIZ588km6du3KCy+8wI033ujZ5i9/+QtGo5GpU6diMBg4//zz+e6774iNbVh5/MEHHzBjxgwuueQS1Go11113Hf/+97+9GkOk5pvRo4hEKe1T46gtqeNEjYWe2d7lhHjE1xAF2qtUKhJjZFG4zuogq/W7+MSpztcYrRqdRoXdKVFvaePiqyfz1X/nKxB256sSO6ALgvM1Tq9hQMdUNhVUs+5IZcjEV2OjmIqIX+1uRJq7SOu9rZ9zxw9/o84mX53OTsjm+h4zWbwOOqalCeE1EBxWWPoIbJCvYNJxuBwzkBramAuBQNC2eeGFFwC5QOOnn35i1apV/PWvf2XXrl0MHjyYX375JbIDFAiiiIbYAS/EV60arAjnayMU52tAsQNR6nytdEcOpMTpTsr89YVgOF93HDMAcuFvxNi7BL6cBhaD3Dcw8WXoe43n106Xk+fXPc/fVvyNTN5HTRz/N+Z1HrroNr+dcHvd4mufEEYtDMxL5XCFkV+PVLFkRzEA1wzs0Mq9BILo4KqrruKqq65q9vcqlYonn3ySJ598stlt0tPT+fDDD/06fqTmm6JwqxVyUmR1vaTG7PV9lMxXf5e2e4Piwg1FCZb1lMxXlUrlEc+MbTz3NdDYgdQ4xTV5el5oKFFiB4IhvgKM7Cq3PIaydEuJHNBr1X5P/ILN5uLNrD3xAwC/FGylzlZH38y+vH3N2xTcX8CE7r8FGgRagR9UHoK3L20QXkffB5O/FcKrQCDwGqfTid1ux2q1YrFYsFqtp+WDCQRnO97GDgDo3CunrML56qFWcb764Q+IVWIHojTztdyT9+r/fFYxZxyvNntctL4gSRI7PM7XCIivDht89xD89w+y8Np+CNy1+iThdXf5bkYvGM2fl/0Zi9NCXKwsmg7NnhDQEuS97tiBPjmhK3ga5C5Qfn9tAbUWBznJsZ7zO4FA4B3hnm9GhyISxeSmyCHZJwzel275ciXaXxJjQleCpTh3G7tDlePVtXHx1RJo7IBbfK0Ns/PV7nG+BieLZGS3DAA2HK0Myv6awmiV30dJEXa9uiQXSw4s4eJ3L2boG0PZXfkrAHmJvVjyxyXsnLaT2wbfRow2hmp3nERafNt1d0eUnZ/B6xdC8TaIS4c/fgKXPgka8XwKBILWuffeexkwYADZ2dnceeednDhxgilTprBlyxbKy8sjPTyBIKpQzB5exQ64L4IL52sDDYVbvguLDYVb0ep8DSzvFSA7KRa9Ro3DJVHsgwlJobjGQkW9Da1aFVIHaJNUH4UF42Hdq/Lt/Blw2/eQ1gUAh8vBMz89w+DXB7P++HqSY5J5+5q3ubz3YAAOldf7fWiDyeYp6+4VQvF1oFt8Vc7NrxnUPiT5sgLBmUik5pvRsxY4Ssn1OF+9F18t7qvKocp8hYbSrbpQOF/d449tJFB6xN4QHC+cBOx8VfJCwy6+yhNDbZCcr0M7p6FRqyiqMnPCYKZ9avCbOOut8nMUqcgBi8PCB9s/YN7aeeyp2AOARqVhWMc+HDoKo9qP44qew066T7Xb0ZwqnK++YTfL7oJNC+XbnfLhurchRSx/EggE3lNcXMzUqVMZO3Ys/fr1i/RwBIKoxuSD2UNZOSUyXxvwFG4FEjsQpeJrhcf56r/4qlar6JgWx+EKI4VVJjqm+RZTtt0dOXBOdpLn+QoLp/YN/GY+9LrC8+udZTuZvGgyG09sBODKnlfy+lWv0zG5Iy9VHQDgUJnR78PvKZZdr3npcV73xfhDn9wkTywgwDUDWy8ZEggEMpGab0bc+frKK6/QpUsXYmNjGTlyJBs2bGhxe4PBwPTp08nNzSUmJoZzzjmHJUuWhGx8SuxAca0P4qsPy4D8JRzO18ZflIlnTOyAEqnQtjJf7UHMfAX59ezXXr4Kvf5IaNyv9W7na7jF10pTJf+3+v/o8kIX7vj6DvZU7CFJn8Sc/Dkcue8Is867E6DJ0jQlTkI4X32g4gC8Nc4tvKrggtlwy2IhvAoEAp/55JNPmDFjRsSE12ifkwoEjTH7cL6h1yjOV99dnmcqyjlUYOJrdIrZDc7XwMwEgZRubT8mRw4M6BimyAGHBZb8GT7+kyy8dhwBd/3sEV7tTjtPrXqKIa8PYeOJjaTGpvLute+y+A+L6ZjcEYDuWYlAYM7XvSXusq2c0Lp9Y7Qa+rodxT2yEjm3fZjdxQJBGyZS882Iiq//+9//mDVrFo899hibN29m4MCBjB8/nrKysia3t9lsXHrppRw9epRPP/2Uffv28eabb9KhQ+hO8tu7YweKDb5nvobyKp/ifK23BFcEdDhdONy5Po0FSo/Ttq2Lr0GKHWhKuAslDpc8bn2QYgegIXogVLmviks6XLEDh6oOMWPJDDq90IlHfnyEUmMpHZM7MvfSuRTNLOJfl/2LvJQ80hLk17CqidxeJXZAOF+9Q7XjYzlmoHQnxLeDmz6DSx4FjVhUIRAI/OP9999n9OjRtG/fnoKCAkAuRli0aFFIj9sW5qQCQWMaYgda/85VYgdszuh0akYCT+xAQJmv0fl8Ks7XjACcrxBY6ZYn7zUM4muCtRTtO1ec0jewBFLzANhaspURb43g0ZWPYnfZuabXNey6exc3D7z5pGzX7pkN4qsk+XehYm9x6PNeFcackwnA74fnBZRRKxCcjURivhlR8fW5555jypQpTJ48mb59+zJ//nzi4+NZsGBBk9svWLCAqqoqvvzyS0aPHk2XLl248MILGThwYMjGmONH7EA4xNfk2NA4XxsH8cc0ETvQlp2vkiQ1xA746XxVRLlwO19tjuDGDkBD6daGI6ERX5X3SkJMaJcarTu2jus/vp6eL/XklV9fwWQ3MShnEP/5zX84fO9hZp83m5TYhomfUqbVVGlag/NViK8tYjcxqOAttF/dDXYjdLkApv0CPS6J9MgEAkEb5rXXXmPWrFlceeWVGAwGnG6hKDU11dNMGyrawpxUIGiMySbPs7zKfPXEDgjnq0JD7IDvz0ncWRA7AI3FV98yXyVJanC+dkgNaAytodr1ORfu/Ruq0h0QnwE3furpG7A5bTz242MMf3M4W0u2kh6XzgeTPuDL331J+6TTl+l3zohHrZKFeaW0zFf2KM7XMOTcTr+oB5/clc/t53cN+bEEgjOJSM03I2ZPstlsbNq0iYceesjzM7Vazbhx41i7dm2T9/nqq6/Iz89n+vTpLFq0iMzMTP74xz/ywAMPoNE0PfGwWq1YrQ0fnnV18tUou92O3d66gNYuXt5vndVBVZ2ZJC8qMU3uL/MYLV4dwx/i3eKhwWQL6jHqzA2ClFpyYnc7RZXj1QT5eP6gHN/XcdidLpSyTo3k8utxJOjkq4rBft5bw2qTj6VVB+89NahDEioVHK4wcryqnqykwCZop1JeJ0/U4vWa08bs72uo4HQ5+frA1zy//nnWHmv4vLi8++XMHDmTsZ3HyleAXWB3nXyMRL38Glab7NhstpOuFFcZ5fd/Uow64u/zqKV8H5rPb6Nz1T4kVLgumIPr/Dmg1oB4ztoMgf4NnunY7XYkyYnL1fqJtSQ5PXMKf+/n7xjPNF566SXefPNNrr32Wv7xj394fj5s2DDmzJkTsuO2lTmpILqI5OeoyyV5lrzrVK3PaZWqA7M18vP4aKHWfb4Wp/H9NdQgP/cWh+u0uWQ0UF4nf86kxp4+B/eF9imyGaGgst6n/RRWmagx29FpVHTLiA3Ne85uRr3sr2i3vAeAs+NIXL95C5JzwW5nc/Fm7lh8BzvLdwJwba9reWn8S2QnZuNwNG0m0gAd0+IorDKzv7iGNB8zKZwuiX0l8ud6z8y4kP+taZDP55p7PG2FQD5Lwz1f8+V+je+r/D9c9wvnnLQtfqdEar4ZMfG1oqICp9NJdnb2ST/Pzs5m7969Td7n8OHDrFixghtvvJElS5Zw8OBB7r77bux2O4899liT93nmmWd44oknTvv56tWr2b17t1djjdNoMDtVfLJ4KTleZI3vKlADaoqLClmy5KhXx/CVE0UqQMPuA4dZ4jwYtP1WWQG0aFUS3333refnZSfkx7R9z36WmJp+fcLNsmXLfNre4gTlLf/j8mX4Y34tNsn7KK8xhjXX7ddy+fU2VFUG9bjt4zQcN6l444sVDGkXXDfEl7vk94y29jhLlhxrchtfX0Ory8ryquV8XfY1xbZiALQqLRemXcjEzIl0iuuEebeZb3d/2+w+5HMVLU6XxGdff0t8o0/BY2UaQMW+7ZtxFQh3yKnkVf7EgKJ3UUs2LNoUNnWZRkV9X/ju+0gPTeAnvv4Nni3U1dVx6Lia2ITWlw1ajHUssxwiKSnJ7/v5Q0VFhV/3i2aOHDnC4MGDT/t5TEwMRqP/BSit0ZbmpILoIxKfo9ZGc9rVPy6ntUVGhip5TrZxy1bUx7aEenhtghqTPOeL1fr+GpocoMwlv/7mW/zs8Q0ZReXyY9u/YyP2o/7v57gRQMuhkhqfzj+2VMjnLbmxLn5Y+p3/A2iGREsxw468TIqlCAkV+7OvZl+73yD9vAW7awP/LfkvX5R9gQsXyZpkpnacyujY0Wxavan1fbvkv5VFP66nco9v5wKlZrA6tOjVEjvXrWJ3dGnyUY8/n6Xhnq/5cr/G9wXCer9wzknb4nw0UvPNNhXM53K5yMrK4o033kCj0TB06FCOHz/Ov/71r2Ynug899BCzZs3y3D5+/Dh9+/ZlzJgxdOnSxavjvnJoDfvL6uk5aAQX9GjX6vYbF++BE0X0OacHV47r4dUxfKV0TQHfHttHelZ7rrxyQND2e7jcCJt/IS5Gx5VXjvf8/OCKg6wsPkx2h05ceWXfoB3PH+x2O8uWLePSSy9Fp/O+GKnSaIMNKwG4ZsIVfl2lLq218I9tq7G41FxxxWVhu9Jt2nwcDu4iNzuLK68cErT9bmYv764txJ7WOaiva7XJxqz1qwCJeydd6Fm2pODra1haX8prm17j9c2vU2mWC8LSYtOYOmQqdw+7m9zEXJ/G9+iW5ZhsToafP5bOjcb2+LYfATuXX3Q+vcKQ1dRmsNWj+e4B1IX/A8DZZQwrE29gzJXX+/Q3KIge7nzhHwABAABJREFU/P0cPVuoqqriyE+HiU9KbXVbU52BSy/oRnp6ut/384ejR4/6db9opmvXrmzdupXOnTuf9PPvvvuOPn36RGhUTROpOakgeojk52hlvRU2rAJg4oQrUKtbno9+Vb2FvTXl9D23P1cO6xiOIUY1VrsT59rlgOx89fU1tNqdPPSrfP+Lxl0a0lZ7f3hw4w+Ai6suPXme6yt1FgfPbl+B0aHigosv82oFKMD27/bBgQLOPzcv6OeNqh0fo/n2SVR2I1JCJtYJL7H3gJzBvaVsC3csvoO9lfJFsxv63MALl71AZkKm1/vfrt7H7l8KiM/pypVX9vZpbN/uLIGt2+ndPoWrJozy6b5nM4F8loZ7vubL/RrfFwjr/cI5J22L89FIzTcjJr62a9cOjUZDaWnpST8vLS0lJyenyfvk5uai0+lOWs7Vp08fSkpKsNls6PWn5zTGxMQQE9OwnLq2Vs5h0el0Xv9xt0+LY39ZPRX1Dq/uY3U3iSbEen8MX0mNlx+Tye4K6jGc7hjgWJ3mpP2mhOh4geDLawjgQl6Sodeqm3yveEO7ZPn5cbokrC5V2CZbLuRJtV6rCerzn989k3fXFrKxwBDU/a4+WIrTJdE7J4nu2c0H7bf2Gu4p38Nza5/j/e3vY3XKS6i6pnZlVv4sJg+aTII+wa/xpcXrMdnM1Nskz/FdLsmT5ZuZEh817/OIU7ITPp0MFftBpYaLHsY16l6s337n89+gIPoQr2HT6HQ6VCoNanXrSw5VKo3nefT3fv6O8Uxj1qxZTJ8+HYvFgiRJbNiwgY8++ohnnnmGt956K2THbUtzUkH0EYnXzy6580p1amJiWp/TxrgzSp2oxHsNMFjk2ACVCmI0vr+GWq0WlQokCRyoo+o5NVodmN2RFLmpCeh0/p/up+t0pCfoqTLaKKmzk54U59X9drlLpwblpQfvubGZYMmfYet/5NtdLkB13VtoYjOw7vuCv/30N15Y/wIuyUVWQhavTXiNSX0m+XyYntlyVuuRSrPPY99fJheTnds+JareE20Ffz5Lwz1f8+V+je+r/D9c9wvnnLQtvtcjNd+MmPiq1+sZOnQoy5cv59prrwVkF8Hy5cuZMWNGk/cZPXo0H374IS6XC7VaFsH2799Pbm6u32KaN+S6S7dO1HgXNq5kMMWFsHArUSncsgQ348XiUMrCTl4/oxRuBft44UQpE4sJYG1QrE5DjFaN1eHCYLKHTXy1u8euC/K6phHu0q39pfVUGW2kJwTn7+j7XSUAjD+36ZPWlpAkiVUFq5i7Zi7fHPjG8/ORHUby5/P+zLW9r0Xj5RdQc6TG6zhuMFNtbMg4rrXYPZnAqfFt70sk6EgSbHoHvnsQHBZIyoXr3oYuo0W2q0AgCAl33HEHcXFxPPLII5hMJv74xz/Svn17XnzxRX7/+9+H7LhtaU4qEEBDua+35xoNhVuuVrY8O1DKthL0WtQq389tVCoVsVoNZrsTqz26ntPKenluG6tTe1XG1hp56fFUGW0UVpno2771EimXS2LncfnCUv+OzRswfKJsD3xyK5TvBVQw9kEY82dQa1h7ZDUz983khPUEADf2v5EXL3+RjPgMvw7VPSsRgENl9T7fd69StpUT+rItgUDgP5Gab0Y0oWbWrFm8+eabvPvuu+zZs4dp06ZhNBqZPHkyADfffPNJ5QfTpk2jqqqK++67j/379/PNN9/w9NNPM3369JCOMydZvspXUmPxanvPhCgIX3jNoYihddYgi6/uscdqTx57giK+Bvl44UR5bDHawIU7wOOSDAcOtyqoa2VZma+kJ+g5J1ueZGw4UhmUfZptTn46UA7AZedmt7J1A3annY92fMTwN4dz0bsX8c2Bb1Ch4tre1/Lz5J9Ze/tarut7XcDCK+ARmatNDeJrtUmZiGsCfo+0eSy18NntsPh+WXjtcSnc9bMsvAoEgjbJM888w/Dhw0lKSiIrK4trr72Wffv2nbSNxWJh+vTpZGRkkJiYyHXXXXeaG7SwsJAJEyYQHx9PVlYWf/7zn08r+1i5ciVDhgwhJiaGHj168M4773g9zhtvvJEDBw5QX19PSUkJx44d4/bbb/f7cXtLW5mTCgQAJps8p43Xe+ej0SniqzO6hMJIUec2k3i7jL4pFKOKct4XLZTXyyvF2iXGBCUeTYkOK6oyebX9kUoj9VYHsTo1Pd1Cpt9IEmz5D7xxkSy8JmbDLV/B2AcxOa3M/G4mY98bywnrCXITc/nq91/xn0n/8Vt4BeieKY/5uMGM2ebba7vH7fjtLaLLBIKoJxLzzYhmvv7ud7+jvLycRx99lJKSEgYNGsR3333nKTwoLCz0uAkA8vLy+P7775k5cyYDBgygQ4cO3HfffTzwwAMhHWduquJ89U589QiY/jQ6eYnH+WoNrgDocYee6nyNbfviazCcrwApcTpKa61hFV+VybIyeQ4mI7tmsL+0nvVHqri8n2/ZqU2xan85FruLjmlx9M1t/cpvnbWOtza/xQvrX6CwphCAWG0skwdNZuaomfTM6BnwmE4lNV4RXxteQ0WIVX531lK8TXYXVB0GlQYueRTOuxfUEb1WJxAIAmTVqlVMnz6d4cOH43A4ePjhh7nsssvYvXs3CQlyhMvMmTP55ptv+OSTT0hJSWHGjBlMmjSJX375BQCn08mECRPIyclhzZo1FBcXc/PNN6PT6Xj66acBucRgwoQJ3HXXXXzwwQcsX76cO+64g9zcXMaPH9/s+E4lPj6e+Hj/swp9pa3MSQUCAJNNno97a/TQu+e+docoE4WG85nE1prKWiBWpwHsnvO+aKHSLb5mJMa0sqV35KXJJqRCL8XXHcdqAHnpvTaQ8xZrPXwzG7b/V77d/WL4zRuQmMnqgtXctug2DlXLhUQXp1/MR7d8RFZylv/Hc5OeoCctXke1yc7hinrObe+de7fGbOe4QV4lK5yvAkHbIZzzzYgXbs2YMaPZJV0rV6487Wf5+fmsW7cuxKM6GSV2oMTL2AHlKlkoYweSQhQDYG3G+aocz9iWxVfF+RqgKJ4aJ4tzYXW+unOEA5rENMOIrum8v66A9YergrK/pY0iB1q64l5hq+DBFQ/y9pa3qbHKE7XM+EzuGXEP04ZPo1186+V2/pLmdi83jh0wuMXXtISzNHJAkuDXt+D7h8Fpg+SOcP0C6DQy0iMTCARB4LvvTm6cfuedd8jKymLTpk2MGTOGmpoa3n77bT788EMuvvhiABYuXEifPn1Yt24do0aNYunSpezevZsffviB7OxsBg0axFNPPcUDDzzA448/jl6vZ/78+XTt2pV58+YBcg7qzz//zPPPP9+k+DpkyBCWL19OWloagwcPbvF7Y/PmzUF8Rk6nLcxJBQJoMHp4e67R4HyNLqEwUiixA4HEh8W6n3tLlMUOVLhjBzITg2Mm8Dhfq70TX7e7xdf+HQKIHCjZKRsBKg+4+wb+CufPot5h4qEl9/Dyry8D0DG5I69e8SqufS7S4tL8P94pdM9MZGNBNa+tPES3TO/cu+V1skmrQ2ocKSK+TCCIOqJhvhlx8bUtoIivxd46Xz25qWHIfLU6kCQpKMtKoGECcerYz4TYgQbna2CvS3Kc/IVqMIVPfLW7na96TXBjBwBGdpNzX/eU1FJjsgc0YbA7XSzfWwbAZX2bjhzYVrKNf/3yL/67+784kf9WerfrzaxRs7hpwE3E6bwL8w+EtPgmYgeM9pN+d1ZhqYGv7oHdi+Tb51wB174K8f61sAsEgvBRV1fnKW6C00udmqOmRj5BVpptN23ahN1uZ9y4cZ5tevfuTadOnVi7di2jRo1i7dq19O/f3+MGBRg/fjzTpk1j165dDB48mLVr1560D2Wb+++/v8lxTJw40TPeiRMnBm0+IxCcySixA946X5VVX3ancL4C1CqxAzGBxA4o4mt0Cdoe52tCcJyvivjqrfN1+zEDAAP8yXtV+ga+fQCcVkhqD9e/DZ3PY8WRFdz+1e0cNRwFYMqQKfzr0n8Rr4lnyb4lvh+rBc7JSWJjQTWLtxf7fF9vcnEFAkH4iYb5phBfvSAnRRaD6iwO6q0OT95qc4TD+aqMwe6UsDpcQRN6G3JRmy7cqjsDCrcCjYOIROarMlkORexAVlIs3dolcLjCyK9HqxjXjGjqDRuOVFFjtpOeoGdYlwbhTpIklh5ayty1c/nh8A+en4/pNIY5581hwjkTUKvCt6xdcb4aROwAHN8En0wGQwGodXDpEzDqbrkCWCAQRD19+/Y96fZjjz3G448/3uJ9XC4X999/P6NHj6Zfv34AlJSUoNfrSU1NPWnb7OxsSkpKPNs0Fl6V3yu/a2mb2tpazGYzcXEnX2B77LHHPP9vbdwCgUCmIfPVR+erKNwCGs5nEoOQ+Rpt4muFkvmaFJz5bJ5bfD1WZcblklC30D/hcLrYdUK+GOiz+GqplbsGdn4m3+55GVw7n1qtjr8svovXN70OQKeUTrx19Vtc2v1SAOwhKIGdcVEPEmO0Pr+2Oo2aP47sFPTxCASCwImG+aYQX70gMUZLUqyWOouDkhozPbJaDtFuzj0aTBL0WlQq+QKhHGoenGM1CJSnxA64JydWhwu70xUSETDUWB1NC8u+kqI4X822VrYMHorzNRSxAyC7Xw9XGNkQoPj6vTtyYFyfLDRqFVaHlY92fsS8tfPYWbYTAI1Kw3V9rmOEYwT3Xn8vOl34l+akuQu3qk6KHVCcr2fJUiFJgvXzYenfwGWH1E5w/TvQcWikRyYQCHxg9+7ddOjQwXPbG9fr9OnT2blzJz///HMoh+Yzd9xxBzfddBNjx46N9FAEgqhGEYW8FV+VzFdRuCXTEDsQgPjqXkkXbYVbFe65bbCcr7kpsWjVKmxOF6V1FnJTml+hdqjciNnuJEGvoWs7H8q2GvcNqLVy30D+PSw98gNTvp7i6YSYNmwa/xz3T5JiQlto1T41joev7BPSYwgEgsgRqflm21PQIkR79xeNN9EDypewt0uB/EGtVpGoD74b1dJMLmpCI7dvW819tdqDEzuQ6hZfa8Oa+Rq62AGQc18B1h+u9HsfkiSxdJfcij26ZyL/+PkfdH2xK5MXTWZn2U4S9YncP/J+Dt57kP9c+x96xPcIytj9oanYgaqzyflqqoL/3gjfPSgLr32uhjt/EsKrQNAGSUpKIjk52fOvNfF1xowZLF68mB9//JGOHTt6fp6Tk4PNZsNgMJy0fWlpKTk5OZ5tSktLT/u98ruWtklOTj7N9Xoq5eXlXH755eTl5fHnP/+Zbdu2tbi9QHC2ojhfvTVfCOfrydQFJXZAfk6t0Zb5Wqc4X4Mjvmo1ajoopVuVLUcPKJED53ZIQdOCQ9aDJMGGN+GtcbLwmpIHk7+lZuit3LF4KuP/M57CmkK6pnZlxc0reHXCqyEXXgUCwZlPpOabQnz1khwl99XQuvjqawi+v3hyX4MqvjbtfNVp1B7HaFuNHmjIfA3Q+drEkvVQYwth4RbAyK4ZAOw8Uet3ru/2YzWU1FrQqB3cuHgYDy1/iOL6Ytonteef4/5J0cwinr/8ebqkdgniyP1DEV8bv4aewq0z3fla9Cu8Pgb2fQMaPVzxL/jt+xCXGumRCQSCECJJEjNmzOCLL75gxYoVdO3a9aTfDx06FJ1Ox/Llyz0/27dvH4WFheTn5wNywdSOHTsoKyvzbLNs2TKSk5M98Qf5+fkn7UPZRtlHSyxatIji4mL+9re/8euvvzJkyBDOPfdcnn76aY4ePervQxcIzjh8jR3QezJfo0sojBTBcL4qJhul6yNaqHQ7X9slBM9M4G3u647jcpb4AG/KtswG+PhmWDJHLnrtdSXcuZollgrOffVc3t7yNgD3jriXHdN2cFHXiwJ6DAKBQKAQqfmmEF+9xNvSLUmSPM7XUMYOQKMcVmvwRMCWluYrxzPa2qr4qrh6A3tdlNiBcGa+Ks7XUMU9tE+NIy89DqdLYlNBtc/333B8A9M+mw9ALeswOgwMyB7Au9e+y5H7jvCX0X8hNTY1yKP2HyW3t9pkQ5JkYfuML9xyueCXF2Hh5VBTBGld4fZlMHKqyHcVCM4Cpk+fzn/+8x8+/PBDkpKSKCkpoaSkBLPZDEBKSgq33347s2bN4scff2TTpk1MnjyZ/Px8Ro0aBcBll11G3759+dOf/sS2bdv4/vvveeSRR5g+fbrHcXvXXXdx+PBh/vKXv7B3715effVVPv74Y2bOnOnVONPS0pg6dSorV66koKCAW2+9lffff58ePSK3WkIgiDYaYge8Ew+VlVPC+Srjcb4GIXYgejNfg+N8hYbc16JWxNftx9zia15qyzs8vkk2Auz5Su4bGP8M1RNf4ZalM5nw4QSO1x2nR3oPVt+6mheveJEEfUIwHoZAIBB4iMR8U2S+ekmuJ3bA3OJ2VocLt5YTcLFTa4TT+aocr9JoC+rxwknQnK9x4Xe+2j3ia+hEspFdMyiqOsb6w5VceE5mq9u7JBeL9y9m7pq5/FT4E7mWV9EDPdrX8+EVSxnXbVzUtlanu90AVocLs91JvF7riSBIC6JTIGowVsKX0+DA9/LtcyfB1S9CrGhkFQjOFl577TWA0/KtFi5cyK233grA888/j1qt5rrrrsNqtTJ+/HheffVVz7YajYbFixczbdo08vPzSUhI4JZbbuHJJ5/0bNO1a1e++eYbZs6cyYsvvkjHjh156623GD9+vE/jtdvtbNy4kfXr13P06NHTSrwEgrMZk9sI4a3RQzhfTyYYsQOKmcNsi57n1O50ec5PMsLsfLU5XOwudpdtNed8lSRY9xose9TdN9AZbljIV/XHufO1cympL0GFipmjZvLUxU8Rr4sP2mMQCASCpgjnfDOo4mtTLbZnCt46Xxtf/QyX89XfZeJNoSydiW0iFzUUxwsnDZmvgYmvSiZoOJ2vdnfsQCiLzkZ0TefTTcdYf6Sqxe3MdjPvbXuP59Y9x/7K/QDE0hm91AmtGr6/4zmSY6N76X68XoNeo8bmdFFtshOv1565hVsFa+HT26DuBGhi4Ip/wNDJwu0qEJxlKC7/loiNjeWVV17hlVdeaXabzp07s2TJkhb3M3bsWLZs2eLzGAF+/PFHPvzwQz777DNcLheTJk1i8eLFXHzxxV7v40yejwoE4HvsgDJ/tArnK9AQO5AYq8Xq5z4Uk000xQ4oRbIatSqoK7m8EV/3l9Zhc7hIitXSOaMJ0dRUBYumwz7390efa6i69EnuWfkIH+74EIBeGb1YOHEh+Xmtx9QIBAJBIARjvukrQRFfrVYrL7/8Mv/6178oKSkJxi6jDiXztaRV8bXBoRhKoQwalsoEVXxtpnALGkq32qr4avFEKrS92AHFqaANofN1lDv3dfsxA2ab87TCuHJjOa/8+gqv/PoKFaYKAFJiUpg2bBopzhuY/2Mx+d3bRb3wCqBSqUiN11FWZ6XaaKNDalyD8/VMiR1wueCX52HF/4HkhIwecMM7kNM/0iMTCASCJunQoQNVVVVcfvnlvPHGG1x99dWtFog15myYjwoE0Dh2QDhf/aHOfS6TGBOI+Bp9sQPl7rKt9AQ9am8Kr7ykQXxtfgWoJ++1Y8rpK9+KNshGgJoiuW9g/NN8lpDG3QtGUWYsQ61SMyd/Do+PfZw4nbhwJhAIQkug801/8Vp8tVqtPP744yxbtgy9Xs9f/vIXrr32WhYuXMhf//pXNBqN13lebZH2qbL4eqKV2IFw5b1Co8zXIMYAKFfEY5twhypLc9ps7IDifA0wDiLVLb7WWx3Yna6Qi+zQOHYgdMfKS48jNyWW4hoLWwqrOa9HOwD2Vezj+XXP8+62d7E45IsPnVM6M3PUTG4bfBtJMUlc+8ovAIw/Nydk4ws26Ql6WXw12TDbnJ73fuqZ4HytL4cvpsKhFfLtAb+DCc9BTGJkxyUQCAQt8Pjjj3PDDTeQmpra7DZn+3xUIIAG56u35xvK/FFkvso0znyt9HMfcR7xNXqeU6VsK5iRAwB5abL4WlFvxWRzNJk1rOS99u+Q2vBDlwvWvgTLnwSXA9K7UXXVc9y16TU+2f0JAH0z+7Jw4kJGdBgR1DELBAJBc3gz3wwFXouvjz76KK+//jrjxo1jzZo13HDDDUyePJl169bx3HPPccMNN6DRhF5wjBQ57szXOouDeqvDI3yeitnHyVAgJMY0iIDBwtqCeJwYAqdtOGmpTMwXkuMaxLlas52MxNBfJXG4lNiB0DlfVSoVI7qms2jrCdYdrsSp28PctXP5et/XSMjHH95+OHPOm8OkPpPQquX3Q0mNha1FBgAu69t2MvkaSrfsHterVq1q9m+7zXDkJ/jsDqgvAW0cXPkvGHyTiBkQCARRz5QpUwA4ePAghw4dYsyYMcTFxSFJksdJdbbPRwUC8D12oMH52nr8yNmAEjsQUOGWEjsQRc7XCrfzNTOIZVsAKfE6kmO11FocHKs2c0520mnb7DhuAGTnK+DuG7gLDiwFQOp3HZ93H8Ndn/2WClMFGpWGB89/kL+N+Rsx2tCfSwkEAoGCN/PNUOD1N84nn3zCe++9xzXXXMPOnTsZMGAADoeDbdu2RW2pTjBJjNGSFKulzuKgpMZCj6ymHWSK8zUuHOJrmAu32nrsQEPhVmCvjUat8rwXDGESXxWnQqhdtsO7pLJo6wleW/MDs9fO8Pz86nOuZnb+bMZ0HnPa3/uy3fLSzsGdUslKjg3p+IKJEi9gMNk84mtqvL7tfp65nLB6Lqz6B0guaNcLfvsuZPWJ9MgEAoHAKyorK/ntb3/Ljz/+iEql4sCBA3Tr1o3bb7+dtLQ05s2bd9bPRwUCaDB7eC2+CuerB7vT5TnfSYrxf7VTNMYOVBpl8TXYzleAThnx7DxeS2Gl6TTx1WJ3sq+kDoD+HVKgYA18ervcN6CNpfaih5l8bBWffzVZ3iarPwsnLmRo+6FBH6dAIBC0hjfzzVDgtZJz7Ngxhg6VPyD79etHTEwMM2fOPKsmug2lW81HD1jDKL4mhUAMbckd2uZjB5RIhQBjByD8ua8NztfQiK/1tnr+vf7fPPLL7wGwWdoTo05k6pCp7Jm+h6/+8BUXdrmwyb/3pbtLgbYVOQANxWlVRlvbL9uqK4X3r4WVT8vC66CbYOqPQngVCARtipkzZ6LT6SgsLCQ+vqGw5Xe/+x3fffcdIOajAgE0Nnt456MRma8NNI5rS4zx/3xNKSeOJvG1ol42E7QLgTGkpdKtfSV12J0SGfFaOu58Fd65CupOIGX05JsLZ9H1lyf5fO8XaNVaHrvwMTZO3SiEV4FAEDG8mW+GAq+dr06nE72+4SqaVqslMfHsyg/MSYljf2k9xS2UbnkyX728Eh0IylKZYGa+euN8NdraqPhqD07hFshL1o9Vm6kxhUd8bch8De7J5Ym6E7y0/iXmb5qPwWIACfJUBtRSKouu38r4Pt1bvH+Nyc7aQ3JaVlsTX9MTZKHVYLJ72mHbZNnWoR/h8ylgLAddAlz1HAz8faRHJRAIBD6zdOlSvv/+ezp27HjSz3v27ElBQQEg5qMCATQ4X08tR20O5eK9VThfPZED8XoN2gBMDcq5XjRlvlbUu52vIRBf81oQX7cfM5BBDe/q30S1YjMApr4Tmeyo5OMVDwIwOGcwCycuZGDOwKCPTSAQCHzBm/lmKPBafJUkiVtvvdXTAmaxWLjrrrtISEg4abvPP/88uCOMItorzleDF+JrgLmi3pDoEV+DJwAqV2+bKqUKRcFXOGmIHWh7zlcloytYztedZTuZt3YeH2z/ALtLfgw903syK38WW/b05Ptd5ew/4WJ8K8bJFftKcbgkemYl0rVdQssbRxmK0FptsmHwxA60Ieer0yFHDKyeC0iQdS7c8A5knhPpkQkEAoFfGI3GkxwIClVVVZ75p5iPCgRgchshfI0dEM7Xk8u2AkE51zNHpfM1BLEDbvG1qAnx1bjvR76NeZwsiwFJG8ea/r/hqj0fYbDWoFPrePTCR3lg9APoNG1oni0QCM5YvJlvhgKvv3VuueWWk27fdNNNQR9MtJPjFl9LapuPHfD1SnQgJIYgdsDiaN4dqoi9xjab+dq8sOwrqXENeaHhQJksa9X+j12SJJYfWc7cNXP5/tD3np+f3+l85uTP4epeV6NWqXnPfpTvd5Wz/kgV97Syz6W72mbkAJwcO1DtiR1oI87X2hNyqVbBL/LtobfC5f8AXVxEhyUQCASBcMEFF/Dee+/x1FNPAXIRpMvl4tlnn+Wiiy4CxHxUIADfOyb0WnnllE2Ir9R6yrYCEwKjMvPV7XwNW+yAywmr/8WUo/9Eo3JRk9iVBzNSmb91PgDD2g9j4cSF9MvqF/TxCAQCgb94M98MBV6LrwsXLgzZINoKDZmvzTtfLW53ZVgyX2NDkPlqbz4XNRRibzgJVuEWQLLH+Rqe58Lhniwrk2dfsDvt/G/X/5i7Zi7bSrcBoFapmdRnErPzZzOq46iTth/ZNQOATQXV2J2uZt22FruTlfvKAbjs3GyfxxVpGscOKIVbaSEoKAg6B36AL6aCqRL0iXD1i9D/+kiPSiAQCALm2Wef5ZJLLmHjxo3YbDb+8pe/sGvXLqqqqvjlF/lik5iPCs52XC7Js9Td19gBu4gdCJ7z1X2uF01RDhVhEl8lSUJVXyrHXh1ZjQb4n2Ms91u3UlK4Db1GzxNjn2DOeXPQqgN7ngUCgSDYeDPfDAXi09AHclNkV1lLsQMWW/gKtxLdDZ3BLMBSrt42lfna5mMH7MGLHVCWpxvM4XK+yrEDvjhfayw1vLHpDV5c/yLH644DEK+L5/bBt3P/qPvpltatyfv1zEokNV6HwWRnx/EahnRKa3K7nw5UYLY7aZ8SKzebtjFST4odaAOFW047rPg7/PKCfDunP9zwLmS0nMsrEAgEbYV+/fqxf/9+Xn75ZZKSkqivr2fSpElMnz6d3NzcSA9PIIgKGi9z9zp2wD33Fc7XhvMm5bzGX+KizPkqSRKV7tiBjBDEDrRPjUOtksVmw86lpH03HYzlODRx/Nl8K5+4zqXE/hWj8kax4JoF9MkUpa8CgSA6idR8U4ivPtDgfG0hdsCTmRoG8VXJfA1q7EDzhVue2IG2WrjliVQIRuxAeDNfbZ7CrdbHXmAo4MX1L/Lm5jept9UDkJOYw70j7uXOYXeSHpfe4v3VahUjuqSzdHcp6w9XNSu+Lt1VAsBl5+a0yZZpJWLgJOdrtMYOGIrgs9uhaL18e/gUuOzvoIuN7LgEAoEgSNjtdi6//HLmz5/PX//610gPRyCIWhqLr7FerubyOF+dkuxabIPztmChdGUkBxw7ID+n0SK+1pjtOFyyWSMU4qtOoyYvRc/19f8h9bNFgERlUi5X1XWj2HUBTs2vzL1sLvePuh+NOvTnwQKBQOAPkZxvCvHVB3JTZedrrcWB0eogoYkrpr5mMAWCcsXW5nBhdTgDXk4vSRK2FkqpPLEDbdT5qizRCoYw7incMoVHfHV4xNfmJ8ubTmxi3tp5fLzrY5yS/D7sm9mXOflz+GP/PxKj9X4J0shuGbL4eqSSaWNPd1Y6nC5+2CPnvV7Wt+1FDgCku4XWequDslp5mVZUFm7t+xa+nAbmaohJhmtegnOvjfSoBAKBIKjodDq2b98e6WEIBFGP0i8Rq1OjVnsnouobzettTldQIrjaKsGOHYiWwi2lbCspVhua17f2BPNdj9NHuxOAr5My+W3dPhLsE0gEpowaz+zz8oN/XIFAIAgikZxvBqc6/SwhMUZLkluAbC73Vbn6GacP/VPbeLmM0Rr4F3/jzKKWYgfafuZr8GIHwuV8VWIHTnW+uiQX3+z/hovevYhhbw7jo50f4ZScXNL1Er698Vt2TtvJ5MGTfRJeAUZ2ld2xG49W43RfRW/Mr0erqTbZSY3XMaJry07aaCUpVotyznK00ghEWearwwbf/xU++r0svLYfDHeuFsKrQCA4Y7npppt4++23Iz0MgSCqMbnF13i99+KhvtH8UZlTnq0oKwYDFV9jPM5XF5IU+edUyXvNDEHeKweWwfzz6WPbSZ0UxxRpONfUH0Kli6NT3PkAXNRTxGAJBIK2QaTmm8L56iM5KbHUldVTUmOhR1biab+3hNH5qvl/9s47PIpyfcP31mx6CJAEEAQRQRBEQQEVK4KICortHCsiNhARrMdzEMsR5YeoKCoqRc/RY28oIkUFCyggqBRRBERKAmmkbp/fH7OzSUjbMluSvPd1censfjPzTTblnWee73mNBpKsJiqcHsrsbjLDFI7sNZYx1RYoNaevy6Po4rSNNnrGDmgNt4qjJr6qwrHZ53y1u+28/vPrPLn6Sbbmb1XfM5q5otcVTBk0hRPanRDW+Y5tl0aqzUyp3c2WfSX0PqJmpuvSLWrkwDk9sjEHEIUQjxiNBjKSrBSWO/03MnGT+Vq0C969AfauV7cH3gZDpkGQIrogCEJTwu12M3/+fJYvX06/fv1ITk6u8f6sWbNiNDNBiB8qfPFfwdxrVH9473R7oQWXE1rsQGrYsQNVX3+H21uncSWaRCTv1eOCLx6Bb58BYKuxDbdU/oPNxk2c3s3F7GEvMWr2dgCOa4L9HwRBaJnEqt4MSHz9+OOPAz7gRRddFPJkmgLtMhL5/UAZ++rJfa1aChSdP8ApCWYqnB5KHeGLgNqyfJPRUKegVt1pW2Z3k5DS1MTX+vNsgyUjUS1soud8Vede5jzEo6tm8dwPz5FXri77T7WmcnO/m5k4YCId0zvqcj6T0cBJnTP54tcDfL+zoIb4qigKSzf7Igd6Nc3IAY1WSRYKy6uapmXEQ+br1kXw4XhwHAJbOox6AXqMiPWsBEEQIs6mTZs48cQTAfjtt99qvGcwGKQeFQSqlrkH2mwL1LrOZDTg8Sr+mrKlUqJT7EB18dvhir34qjlf2+jlfC3+SzUC7PkBgBeMHh5wtSdNyaFHqwy+vO5JfthZhKJsp326jbapLVjRFwShSdFYvRkpAvqrM2rUqIAOZjAY8HjiI/cmUrRLUxvc5NYTO6AVRFETX21mDpQ6dMlh1Zyhdble4TCnrcNN60gsa4kQjeXZBkt6UlXma6QbF3i8CtrK/34vH0+F5yAAHdM6MmngJG488UbSEtJ0P++ALqr4umZHITcOPsr/+uZ9JewtrsRmMXJ6t7a6nzeaqA22yv3bWiO1mOB2wNJ/wQ9z1e0jToJL50NGp9jNSRAEIYp8+eWXDb5vNAb297sl1KNCy0UzeiQGIb6CGj1Q6fX46+GWSlXma3g1n8Vk9AvalS4P6cR29VSBT3zVxfn662K134C9mFKDkeuVMt5X3JxyRCf27gS3MwOjwcgvew4B1FohJwiCEM80Vm9GioDEV6+3Zf+Rrk5Ouiq+1p/5qn6tohE7AFWFgx45rNrcGxKOk31O26aW+1o9z1aPhluaSOf0eLG7vEEXwIHy3V/f8X/fPg1cB0Clu4y+7fpy9yl3c1nPy7CYIlfoDTiqNQBrdxXi9Sr+pg5LN6uRA2cc0zZi1x0tqjtdU23m2EUoFPwB746B/T+p26dMhHOmQgQ/X0EQhKaG1KOCUJX5Guy9hsVkoNKl1q4tmarYgfDT92xmI+VOT43otlhx0Bc7EJbz1e2E5dNgzRwA1hm8XK6Ukp+QwtyhMxnd/Tr6Pbqc3BI7dpeHn/eq4mufIzLCnL0gCELzRzJfg6R9hia+1hM74ArtaXSoaA3ASnVwvtoDcO2mJpg5qJPTNprUEF91cL4mWU2YjQbcXoXiSieJ1sSwj6nh8Xr4aNtHzPxuJqv3rMagJNLJJ75+dtUihh59dkSdthq92qeRZDVxqNLFtrxSjm2nums/1yIHeuZEfA6RJjO5StxsFavIgU3vw8cTwVkKiZlw8YtwzLDYzEUQBEEQhLgmlNgBAKvZBLhbfOxAqU6xA6DeM5U7PdjdsRdfq5yvIYqvh/UbeAoH9yoOzj56GF9d+BKd0juhKAopCWbKHG72FFXy855iAPqI81UQBKFRQvqrU15ezsqVK9m9ezdOp7PGexMnTtRlYvFKTroqstUXO1AlYEbHQaflsJbq4ER1BLAsP8VXqJQ7m5r4qn4uRgOYjeELlwaDgYwkC/llTg5VumiXHr74WuGqYOHGhcxaPYs/iv4AwGqycsWx17NqrTpmSNfoCK+gLqfqd2Qrvv49n+93FHBsuzR25ZezLa8Uk9HAOcdmRWUekaS64NoqzIZ1QeOqhM//Aevmq9udBsHoeZDeIbrzEARBaKK05HpUaLmEHjug1o8SO+BzviaEv7pIM6xoqwdjiZb52jaU2IEtH6N8NB6Do4RCFK6nklW2ZF4c9jxj+o7x33sYDAY6ZiaxdX8Jm/Ye4s+CCgB6S7MtQRCERglafN2wYQPnn38+FRUVlJeXk5mZSX5+PklJSWRlZTX7Yrd9I7EDUW+45RND9XCiasJxQ8vyk636OW2jicOlCcsm3cTLtERVfC2uCK/pVl5ZHs/98BzPr3uewspCAFrZWnHbSbcx4eQJGJUMTl67AqNBzd2NJgOPas3Xv+fzw65Crj+1C0u35Ppez4yP5lRhUv0aWiVFcYl//u/wzvWQt0ndPm0ynPUAmGQxgiAIQiC09HpUaLlUxQ4EVzNYfeaKlu58LdPV+ap+TbX7v1iS74sdCMr56nbA0n/CDy9hAFbj5koq6X3M+Wy+YC4d0mobAjplJrJ1fwmf/rLft53ULO4JBEEQIk3Q9sw777yTCy+8kKKiIhITE1mzZg1//vkn/fr1Y+bMmZGYY1yhZb4eqnRRUYf7U1t2Eq3MV835WuYITwCEwFy7frG3iWa+JujoSNZyXw9Vhva133JwCzd+fCOdnu7Eo18/SmFlIUe1Oornhj/HX3f+xaNnP0pOSg4uj9ptKxZ5pCd3yQTgh52FKIrSrCIHoKbgGrXYgZ/fhrlnqMJrUhu4+j0Y8qAIr4IgtEhOPPFEioqKAHj44YepqKgIaL+WXo8KLZdQYwcsvjrS0YKdrx6vQrlPKNUrdgCIq9iBgDNfC/5AeWUI/PASAE/gYKTNyqMXv8qivy2qU3gFVWwFWPmb2gBYmm0JgtAUCLXe1JOg1ZyNGzcyZcoUjEYjJpMJh8NBx44dmTFjBv/4xz8iMce4ItVm8QuedblfK52+hlvRynzV0/kaSOyA79rLm5z46nP16pD3qpGuia9BOF8VReHLnV9ywRsX0Ov5XszbMA+nx8nAIwby3uXv8duE3xh/8niSrcn+fVy+z8UaA/G1zxHpJJiN5Jc5WbOjkB93q7+wzu2ZHfW5RILqUQMZkXa+Oivgownw/jhwlUPnwXDLN3D0kMieVxAEIY7ZunUr5eXlADz00EOUlZUFtF9Lr0eFlkulz/wRdOyA3/mq6D6npkL1+yWtaXE4aOKrI8YNtyqdHr+o3CaQ2IFN7+N58TQMuT+Tj5fzqWB1j/P4afwWrjn+mgZXCWriqxZf0UciBwRBaAKEWm/qSdCP/CwWC0aj+sc7KyuL3bt3c+yxx5Kens5ff/2l+wTjkXbpNn4/UMb+Yjtd26bUeM/vHjVH1/mqS+ZrAA23/E7bJhY7YK8WO6AX2hKbQJyvLo+Ld7e8y8zVM/lx/48AGDAwqsco7jrlLk7peEq9+7p93Z3NpuhGDoD69TqxUytW7yjgscVbURRVkG2foV+DsVhSI/M1ks7XA7+qMQMHtwIGOOMeOONeMEbn94QgCEK80rdvX8aMGcNpp52GoijMnDmTlJSUOsdOnTrV//9SjwotlarYgdCcry0587XEl/eaYDZiNRtxhSmaJsZJ5quW92o1G/33anXiqsTz2b2YfnwVE/A1bm6z2fjHiJe48rgrA4pm6+gTXzXE+SoIQlMg1HpTT4IWX0844QTWrl1Lt27dOOOMM5g6dSr5+fn85z//4bjjjovEHOOOHE18PVRZ6z1tKVC0nK+6Zr76irGGhGPtfHqIvdEkks7X4kpnvWNKHCW88uMrPPP9M+w+tBuARHMiY/qOYdLASXRr3a3R8zjdqkPBEgPnK8CAozJZvaOAX/YeAmBYr+YROQCHxw5EyPm64XVYfBe4KiA5C0a/AkedEZlzCYIgNDEWLlzIgw8+yCeffILBYOCzzz7DbK5dnhoMhhrFsNSjQksl1NgByXyt6lmhh+sVqqLa7DF2vlY120qoX0DN/52KNy4nqXAHXhQew8nPx57P8hEvkJ0S+Iq2ToeLr+J8FQShCRBqvaknQYuvjz32GKWlpQD8+9//5tprr+XWW2+lW7duzJ8/X/cJxiPtfLmvuYfFDrg8XjxeVSiLWsOtBP0yWB2BZL422dgB/TNf0xvIfN1TsofZ389m7vq5lDhKAMhKzuL2k2/nlv630CapTcDn0Zyvlig329LQcl81hvVqHpEDcHjsgM7OV0eZKrr+9D91+6gz4ZKXISVL3/MIgiA0Ybp3786bb74JgNFoZMWKFWRlNf57UupRoaWiNXcKOnZAnK+U+pyvaTrkvUJVk+LKGIuvBf5mW3XXss4N/0VZdAdJXjcH8DLelsDlF87jn70uC/pcHVolYjCAosBRbZN1E7IFQRAiSaj1pp4E/Zenf//+/v/PyspiyZIluk6oKdAuXV1yve8w8bX6H95oNdxK1bEBll+gbMj5qqPY2xguj5ef9xyizxHpYbs+Ha7GXb3B4ne+Vst83Zi7kSdXP8mbm97E7VW/Rj3a9GDKoClc3edqbGZb0OfRHAoWHV27wXBip1ZYTUacHi9HtUmuFbXRlNGapoHOsQN5m9WYgfzfwGCEs/4Bp02WmAFBEIQG8HoDF4WkHhVaKqHGDmjOV6c4X3VptgVV9xXxEjtQq9mWs4ID715P1m+fA/AFbt7pMZTnL3yJtsltQzpXgtlETpqN/YfskvcqCEKTJJh6U0+kvXYIVDlfa8YO2H3FkNEAlijlc6YkqOKRLrEDQThfyxyRf8K74NudPLb4V/51QU/GntYlrGP5Ywd0dL5qDZqKK1ws2b6Emd/NZMXOFf73z+x8JlMGTeH8budjNIR+Xq0xQqxiB2wWE8d3TGftriKG9soJKA+qqWA2GUlPtHCo0kVmsg7iq6LAj6/BZ/eA2w6p7WD0POh8avjHFgRBaAH88ccfPP3002zduhWAnj17cscdd9C1a9cYz0wQ4gPN+ZpkDe42Trs3adHOV4dqmGhusQMF5T7na7Va1r5vI8X/GUVOZRFeFGZZLHQdNZ8Xeo0O+3ydMpPYf8hO7yMywj6WIAhCLIhFvRm0+NqlS5cGxZcdO3aENaGmQI5PfN1fj/M10WKKmkCVqmMGqz2AhlvJ/oZbjTeZCpftB9QOdLvyy8M+ViCu3mBJT1QLru/+/IXXXx8HgMlg4rJelzFl0BT6t+/f0O4BozlfzTGKHQC4e1gPXv/+T24cHJ4IHo/cPaw7W/eX0CMnNbwDOUph0STY9K66ffQQuHguJAceMSEIgtCS+fzzz7nooovo27cvp56qPrT69ttv6dWrF4sWLeLcc8/1j5V6VGiphJ75qo5vyZmvheXq/UuGTjn//oZb7tiKrwdLfc7XVNX5+vuKaRzx9VPkAPvxsvCoU7n5sjfITMxs4CiBc9tZR9Mm5S8uPqGDLscTBEGIJsHUm3oStPg6adKkGtsul4sNGzawZMkS7r77br3mFddond4PF1+1JSfRarYFVU7UUh3EUG3+DTWl0jPmoDGKfMv59bi2KvE1fPdoUWURL657kWe/excrD+NyJZOSlMK4E8dxx4A7ODLjyLDPUR23z/lqjVHsAKi5r4dnvzYXrh6ow+e1/yc1ZqBwBxhMcM6/4JQ7wBi7z0wQBKGpcd9993HnnXfy+OOP13r93nvvrVEMSz0qtFQqnGoNHmx/CXG+QkF9y/NDRPsMtNWPsUJzvrYyV7D2uX6clL8dgJUmE46Lnuf+46/S9XxnHNOWM44JLbZAEAQh1gRTb+pJ0OLrHXfcUefrc+bMYd26dWFPqCmgOV8PVbqocLr9y34qA3CO6o0mhtpdXlweb1hL06uW5jfufC2PQuxAcYVaSJTqEKmgNRMLR3zdUbSDp9c8zfwN8yl3lWNUkukImEhj+4Q/yU6NjDjpjAPnq1APigJrX4HPHwCPA9KOgEvnQ6cBsZ6ZIAhCk2Pr1q28/fbbtV6/4YYbePrpp2u8JvWo0FKpih0I7n5Dq4FbtvO19vL8cKiKHYhx5mupg+6G3Zz97TiOVsrxoPBRu+M4+9pPyNDJ7SoIgtBcCKbe1BPdbFnDhw/nvffe0+twcU2azeJ3nFZ3v2rFUDTFV00MBSgP042qFQ4NzV9Pp21jaM7XEl2dr8F/Nt/v+Z7L37mcbs9249kfnqXcVU6f7D4sGPWCv5B1uoJvpBUo7hhnvgr1YD8E71wHi+9ShddjhsMtX4vwKgiCECJt27Zl48aNtV7fuHFjwB1pW1I9KrRMQo0d0OrIlux8zS9TxdfMFL3E19jHDpQ5Sum+/z98ZP0XRyvl7DcYWDf0IS65+TsRXgVBEOpAj3ozFHRruPXuu++SmdlyfsHnpNvYfqCM3EN2f/d3uyu07qPhYDEZsVmM2F1eSu1uMsLo2B5Iw63qsQOKokQ021ZX56smvgbYcMureFm0bREzV8/km93f+F8f1nUYd51yF+d0OQeDwcArS79kd2EFeSV2OmYmhT3PutAcCiK+xhF7f4R3x0DRLjCaYchDMGg8NKNmZIIgCNFm3Lhx3HTTTezYsYNTTjkFUDO4nnjiCSZPnhzQMVpaPSq0PCpCNHv4xVffQ/2WSGG5GjvQOlnn2IEYNdz66tdFlLx3A9MUJxhgQ/IRdB37CQMym1+PBkEQBL3Qo94MhaDF1xNOOKGG4KYoCrm5uRw8eJDnn39e18nFM+184mt152ssxFeAlAQLdpcj7BzWQNyhmtPWq6hO2Ujl2yqKUi3zVQ/xNbDYgUpXJa/+9CqzVs/i98LfAbAYLVzV5yomD5xM7+zeNcbnpNnYXVhBbom9rsPpgtMvvoqwF3MUBb5/EZb+C7wuSO8Ely2AI/RpriYIgtCS+de//kVqaipPPvkk999/PwDt27dn2rRpTJw4scZYqUeFlojHq/jr9eAbbonzVctGba2z87UyyrEDJY4Snv3oRi7fspgzMeFWjMxwX8G4m58iLS0xqnMRBEFoagRTb+pJ0OLryJEjaxS7RqORtm3bcuaZZ9KjRw9dJxfPtPPlvu4vrvS/5s98jWLDLVDdqPll4YuvgThfkywmDAZVgyp1uCImvpbY3Xi86pP5kkodYgdcDQvLB8oP8Pza55mzdg75FfkAZNgyuKXfLdw+4Hbap7avc7+sNPXJeV6JI+w51ocWO2AW52tsqSyCjybAr5+o2z0ugJHPQWKr2M5LEAShmWAwGLjzzju58847KS0tBSA1NbXOsVKPCi2R6g5LredEoGjO15ac+VpQFqnM1+g5X5du/5yV717LVHslCZgosCQzruxuNnAM96ZELgZNECKJ1+ulsLAQi8US0PiMjAyM0thYCJFg6k09CVp8nTZtWgSm0fTISVefKu6v5nj0i69R7kqv5bCWhekQtfuehNsacL4ajQZSrGZKHW616VaEvke1yAGAMqcbr1fBGEbDqfqcr9vytzFr9Sxe+/k17G71s+yc0Zk7B97JDSfcQIo1pcHjZqepRc6BCDpftSLZKuJr7NizDt4ZA4d2g8kKQ/8NJ4+TmAFBEIQI0VgRLPWo0BLRIgcg+CayCS3c+Wp3efxGldYpOsUO+O6ZHFEQXw/ZD/HPzyZy+k/v8G8sgIGDHU+m8OxX+HHuJlonWzFJc16hiVJeXs4zn/1EUmpGo2Pt5aVMvuAEiRgSdCEaoqtG0OKryWRi//79tYJoCwoKyMrKwuOJXeB4NNGcr7l1NNyKlBu0PvxNsMKNHfAVDo3loiYnqOJruGJvQ2iRA6C6bMucbtJsgT0Jqwu/89ViRFEUvtn9DTNXz+TjbR/7x5zU/iTuPuVuLj72YszGwH40cnziayRjBzTx1SyxA9HH64U1c2D5NPC6oVUXNWag/QmxnpkgCEKLRupRoSXiv9ewmII2JWjxVS3V+VroixywmAyk2fRpe6Ld89kjHDuw+PfFzPlwLM+Wl3EUFtwGI55zptL21En8ul1dsddGJ0FZEGJFYkoqyWkZsZ6GIESMoP/yKErdIe0OhwOrVZ8lHE0BTXzdVy12QMtginrmq00f56s2/8YC/FNsZihRYwciRVE15yuo0QNhia++a9uS/xMDXvkba/etBcCAgQu7X8iUQVMY3Glw0A3EqmIHIim+qj9z0nArylQUwge3wO+fq9u9LoYLnwFbemznJQiCIEg9KrRIKlxqrR9s3itUraBytHDxNTPZqlvDYH/sgDsyD3uKKouYtOQOMn56iw9IwIoRe0o2tiv/h/mIfgDkl/maiOmUYysIgiBEhoDF19mzZwNqPsIrr7xCSkrVcmyPx8OqVataVMZWO1/sQHXHY2WI3UfDJVWLHQhTDPVnvjYQOwBVTttyR+RcJcWHia/hNN0qc5ax9eB2IJl5G16kzLwWm9nGdcdfx50D76R7m+4hH7sqdiCSma9awy0RX6PGn6vhvbFQshdMCXDedOh/g8QMCIIgxBipR4WWTDir7Cy+2AFXC40d0ETKzGT9HKJaL4lKp/73RB9v+5h7F93E9LISRqHeb7i7n49t1AuQmOEfp+XYivNVEAQhvglYfH3qqacA1Wnw4osvYjJV/dG3Wq107tyZF198Uf8ZxintMtQ/gsUVLiqdHhKtpqrM12iLrzo5XwNpuAXVMmYj6Xwtr3nsUMTXfaX7ePb7Z3lx/YtYD00mkRNJTrAx5bQHue2k28hKzmr8II2gia+Rdb5q4qsIfxHH64Vvn4Iv/g2KB1ofDZcthJzesZ6ZIAhCs8blcnHeeefx4osv0q1bt3rHST0qtGSqxw4Ei+Z8dbZQ52uVSKmfQ1S759Oz4VZBRQETl0zkj5/fYgmJHIkFr9GCcdhjmOvoN3BQnK+CIAgBE2i9GQkCFl937twJwFlnncX7779Pq1Ytu8N3aoKZZKuJcqeH/YcqOaptil98jVXsQIlOsQMJATpfI5n5Wtv5GrjQu+nAJp5c/SSv//w6Lq+6X2dzOooT5l7wLCP7HqnbPLN9sQPlTg+ldhepYUQj1IfLK7EDUaHsIHxwM/yxQt3ufTlcMAsSohfCLQiC0FKxWCz8/PPPjY6TelRoyWgNt0KKHdCcry1UfNViB1on6ydS+jNfdXITv7/1fW775BauLj/EQpKwYMDbqjPGy16F9n3r3Eecr4IgCIETaL0ZCYJWc7788kspdFGXu+Uc1nRLe+qZaI2uSJaSoAp+ZWE03FIUJWDna7Lf+Rq52IHqDbcAShoRXxVFYfmO5Zz33/Po/UJvFm5ciMvr4rROp/HhFR/SO+tEAFJtNl3nmWQ1+53HeRGKHtCWh0nDrQiy6xt48TRVeDUnwkXPwiUvifAqCIIQRa6++mrmzZsX0FipR4WWiN/oEUbmq7Olxg6U6x87YDNXfU293rpzqAPhYPlBrnj3Cm5661JeKS9jJjYsGKDXJRhv/rpe4RWq4hTaivgqCIIQEMHUm3oSdMOt0aNHc/LJJ3PvvffWeH3GjBmsXbuWd955R7fJxTvtMxL542A5+w4XX5tgwy2XR0GrGRIamb8/5iCKDbfqix1wepy8tektnlz9JD/l/QSA0WBk9LGjmTJoCgOOGADAC0tWAY27ekMhO81Gqb2MAyV2js5KaXyHIHH7PhirOF/1x+uBVTNh5eOgeKFNdzVmILtnrGcmCILQ4nC73cyfP5/ly5fTr18/kpOTa7w/a9Ys//9LPSq0RMKJHbD4YwdCFwmbMoU+h6iey/OrR83Z3R6SrMHdWiuKwtub32bCZxPoXl7EBpLpiBHFlIBh+BPQ7/pG+w0UROC6BEEQmjPB1Jt6ErT4umrVKqZNm1br9eHDh/Pkk0/qMacmQ06a5nytBKoKosbES72pargVuvhavUtngjnAzNeIxg6owq7VbMTp9tYSX8s95Ty55kmeW/sce0v3ApBkSWLsCWOZNHASR7U6qsb4qkgF/QXM7LQEth8oI680MrmvWjaX2Sjiq66U5sH742DnSnW771Vw/v+BNbnh/QRBEISIsGnTJk48UV2p8ttvv9V47/Du5FKPCi2RCqdaDwcr8kG12IEW6nwtiEDsQA3x1eUlKYhD55Xlcdvi2/hgy/vci5VHSFZvzFsfjeGyVyHnuICOozlfJXZAEAQhMIKpN/Uk6L/cZWVlWK21/7JYLBZKSkp0mVRToZ0vdmC/z/kas8xXnxhaGob46nCphZjB0LhAGZ3YAbVA6pSZxPYDZZRUqmLsn8V/8tTqp5i7eS52r/p1z0nJYeLJE7m5/81kJmbWeTzNlRwp5ytA7qHIxg5YzBI7oBs7voL3xkH5AbAkwYhZ0PdvsZ6VIAhCi+bLL78MeKzUo0JLpNJXr4cSO2Bp8Q23tMZU+omUJqMBi8mAy6ME3HRLURTe+OUNJi6ZiKmiiCUkMxTf59nnCrUmTQhsJZ2iKOJ8FQRBCJJg6k09CdpK17t3b956661ar7/55pv07Nmyluq2y0gEqsRXu1YQxSx2IPQYgCpx0tio2p8ShdgBzfnaKTMJgB2F+/nbe3+j6+yuPPPDM9i9dnq26cn8i+az645d3D/4/nqFV6jmfG0kzzYUNPE1ryQyzlctdsAiztfw8bjhi3/Da6NU4TWrJ9z0lQivgiAIccT27dv5/PPPqaxUVxYpSu1l0lKPCi2RSp/zNZR7jZbecMvvfNVZpNTcr4GIr/tL9zPqrVFc/cHV9K44xGZjhiq8mhPhoufg4rkBC6+gNlvWxHRxvgqCIARHIPWmngTtfP3Xv/7FJZdcwh9//MHZZ58NwIoVK/jf//7X4vK1cg5zvtrDCMEPhxQdYgccbq3ZVuNz12IOyqPgfPUYDwDw4dbPybe+CcDZnc/mNONpPHDFA3W6XurCUU1c1pvsVLXYORDh2AGLNNwKj5L98N5Y+PNbdfvE62D4E2BJjO28BEEQBAAKCgq4/PLL+fLLLzEYDPz+++8cddRRjB07llatWtWIE5B6VGiJVPgizpKk4VbQ+B2iOsYOgHrvVGp3+1dA1oWiKLz202tM+nwSJZXFTDMk8i+sGL0eaNtD7TeQdWzQ59bcvCkJ5oDu4QRBEITg6k09CVqJuvDCC/nwww/Zvn07t912G1OmTGHPnj0sX76cUaNGRWCK8Uv7dFW08We+ujQBM7oOxVQdGm5prt1AxMlkHWIOGqLEXuEvLj/4/SUATKRwdZ+r2XDzBpb8fQknpp0YVB6H5nyNRGFSFTsQIeerlvkqDbdC5/fl8OKpqvBqTYHR8+Ci2SK8CoIgxBF33nknFouF3bt3k5SU5H/9iiuuYMmSJTXGSj0qtEQqwzB6tGTna4WzShzVM3YAqu77tHupw9lTsocRb4zg+o+uJ6HyEGsSsnlQsWBEgb5Xw7gvQhJeAfJ9gnIbiRwQBEEImGDqTT0JPq0dGDFiBCNGjKj1+qZNmzjuuMDCwZsDmvO1qMJFpdPjb7gV7SePmvO13OnB41UwGYN3SAbjfK1quKVv7EB+RT4vrH2B59b8l0RmoeDBaikDF/TLPo3/XPwvAFyu4M7r9nj9S/cj4nxN12IHIpT56utKaxXxNXg8Lvjy3/DNU+p2Tm+4dCG0OTqm0xIEQRBqs3TpUj7//HOOOOKIGq9369aNP//8s9Z4qUeFlkZlGM5XbQWVowU6XzXXq9VsJFnnFYo2Xz8Jx2HOV0VRmL9hPpOXTqbEUcJwg413LBkkOyrAkgwXzILjrwzr3JHIsRUEQWjuBFtv6kXYak5paSkvvfQSJ598Mscff7wec2oypNnM/uInt8ReFTsQo8xXgHJnaG5U7WmtLYCGVCk6xw5sL9zO+E/H0+mpTkz9aipFFWohkWhVePPyBQA43KF/q1ZvLBDJhlsHSu0RyQnRHArScCtIDu2BhSOqhNeTboSxy0V4FQRBiFPKy8trOBA0CgsLSUhoWFxoyfWo0HLQVoZJ5mtwaHmvbZKtuney1lzIdnfVfdHuQ7s57/XzuHHRjZTbS5ifehSfehNIdlZAVi+130CYwitAvk98FeerIAhC4IRTb4ZDyIrWqlWruPbaa2nXrh0zZ87k7LPPZs2aNXrOLe4xGAy003JfiyurGm5FOfM1wWzyF1ShRg/4G24FEJlQ1XArvNiB7/76jkveuoRjnj2G59c9T6W7khPbncjUwU8A0CE9nZzUdABKKkN32TqqLQOyRsD52tb3tNnlUSiq0L8JmVYkm6XhVuBsWwIvngZ/fQ8JaWqW1ognwWKL9cwEQRCEehg8eDCvvfaaf9tgMOD1epkxYwZnnXVWnftIPSq0JCr8sQPBL15syZmvheWRc4hqxpVKpxdFUZi7bi69nu/F0j+WcpTJxs5WxzGmJB8DCvS7HsatgLbH6HJuLXZAnK+CIAiBE0q9qQdBqTm5ubk8/vjjdOvWjcsuu4z09HQcDgcffvghjz/+OCeddFKk5hm3tPPlvu4pqvQ7LANxj+qN1gSrNETx1Z+JGoTztczhxusNzunp8Xp4f+v7nDLvFE6dfyof/PoBCgrndzufL679gnXj1tEv+3QAWiVZSbNZgNCvC6quzWIyhBTJ0BhWs9H/xDkSua9uX+yARWIHGsfthM8fgP9dAZVF0K4v3LwSel0c65kJgiDElFWrVnHhhRfSvn17DAYDH374YY33r7/+egwGQ41/5513Xo0xhYWFXHXVVaSlpZGRkcHYsWMpKyurMebnn39m8ODB2Gw2OnbsyIwZMwKe44wZM3jppZcYPnw4TqeTe+65h+OOO45Vq1bxxBNP+MdJPSq0VOzhNNzyGRC8CniCrN+bOppImalzsy2oMq78dSiXIf8Zwi2f3kKZs4zJbY9nmzmLjkW7q/oNXPiMrv0GqpyvIr4KgiAESqD1pt4ErOZceOGFdO/enZ9//pmnn36affv28eyzz0ZsYk0FLfd1Z0G5/7VoO1+huhs1NOdlUM7XhKqn7RUNdPasTrmznDk/zKH7c90Z/fZoVu9ZjdVkZewJY9l822Y+/funnNXlLAwGg989mpFk9TcTq3R5Ql4mpeXZRiJyQCMr1Zf7Wqq/+OqPHTBJ7ECDFP0JC4bD6ufU7QG3wtilkHlUbOclCIIQB5SXl3P88cczZ86cesecd9557N+/3//vf//7X433r7rqKjZv3syyZcv45JNPWLVqFTfddJP//ZKSEoYOHcqRRx7J+vXr+b//+z+mTZvGSy+9FNAcjzvuOH777TdOO+00Ro4cSXl5OZdccgkbNmyga9eugNSjQsumwqWaEUKJHaj+EL+luV8LyzWHqP7iq9Zw658rHuKLnV+QakpkbZcRPHlgJ2Z7sdpv4OZV0PtS3c9dIA23BEEQgiaQejMSBLxm5bPPPmPixInceuutdOvWLWITamq018TXg1XiaySaOjVGSpjOV3/mawDFnM1ixGQ04PEqlNndNcTYw8kry+O5H57j+XXPU1hZCEBmYia39b+N8SePJyclp9Y+RRVqIdEqyeIXX0GNVGgVwhNrzfkayc8lOy2BLfvhQEkkxFdxvjbK1k/go9vAfghs6TDyeTj2gljPShAEIW4YPnw4w4cPb3BMQkICOTm1/y4DbN26lSVLlrB27Vr69+8PwLPPPsv555/PzJkzad++Pa+//jpOp5P58+djtVrp1asXGzduZNasWTVE2oZIT0/ngQceqPd9qUeFlow/8zUM5yuo/RASib5ZJFb4G1Pp7HzdXridb/d8BfTE6VG49MhBvOYxk7jja3XASeNg6KMRi70S56sgCEJoNFZvRoKA1ZxvvvmG0tJS+vXrx4ABA3juuefIz8+P5NyaBDm+2IGd+ar4mmgx6R7kHgjVowBCocod2vi3hMFgaPR8Ww5u4caPb6TT05149OtHKaws5KhWR/Hc8OfYPWk3j5z9SJ3CK0CxJr4mWzGbjP6lVSX20Fy9WuZrZMVXn/O1xKH7sf2Zr+J8rY3bAZ/dC29dpQqvHfrDzV+L8CoIQouhtLSUkpIS/z+HI/S/Q1999RVZWVl0796dW2+9lYKCAv97q1evJiMjwy+8AgwZMgSj0cj333/vH3P66adjtVYJHMOGDWPbtm0UFRUFNIeioiJmzpzJ2LFjGTt2LE8++SSFhYX+96UeFVoy4cQOmKtFb7U052uBztmoHq+Hp9c8TZ8X+nCgfA8A0zr04O2CfSTu/8nXb+BVGDEzov0GtEZieovKgiAIzZ3G6s1IELAaNXDgQF5++WX279/PzTffzJtvvkn79u3xer0sW7aM0tLSSM4zbmmXUTN2wBbAsv1IoDlEQ2+4FbjzFeoWexVF4cudXzLijRH0er4X8zbMw+lxMvCIgbx3+Xv8NuE3xp88nmRrcoPHroodUPNetWsL2dWrCcshLNEKFE18zY2I81X9bKzifK1J4Q6YNxS+f1HdHjQBxnwGrY6M7bwEQRCiSM+ePUlPT/f/mz59ekjHOe+883jttddYsWIFTzzxBCtXrmT48OF4POrf0NzcXLKysmrsYzabyczMJDc31z8mOzu7xhhtWxvTEKtWraJz587Mnj2boqIiioqKmD17Nl26dGHVqlWA1KNCy8bfcCuEmtZgMPhryVCjvJoqeoqU2/K3cfrC07nz8zupdFdyZGprHjD/l8m5L2KoLIL2J6gxA71GhX2uxsgv9TlfU8X5KgiCECiB1JuRIOhWmcnJydxwww3ccMMNbNu2jXnz5vH4449z3333ce655/Lxxx9HYp5xSztf7ID2BDmUYkgPwnW+apmvgYrH/vPZ3bg8Lt7Z8g5Prn6SH/f/CIABAxcfezFTBk3hlI6nBDUXv/M1SS2Q0mwW8kocTcL5GsnYAbOIr1Vs/gA+ngiOEkhsBaNehO7nNb6fIAhCM2PLli106NDBv52QENpN+JVXXun//969e9OnTx+6du3KV199xTnnnBP2PANh/PjxXHHFFbzwwguYTGo95fF4uO222xg/fjy//PKLf6zUo0JLJJzYAVCjB5web8tzvpb7YgfCyEb1eD3MWj2LqV9Nxe62k2pNZe5p/+D0NR/RwbxFHTTwNhjyEJgj70S1uzyU+u772iSL+CoIghAowdSbehKWmtO9e3dmzJjBnj17ajVlaCm0S6vZsdIWg2ZbUNVwK2x3aIBNqZIT1HH/+/l9us7uylXvX8WP+38k0ZzIbf1v47fbf+O9y98LWniFqlD8Voc5X0sqIx+pECrZaWrRE8nYAWm4Bbjs8MlkeOd6VXjtOBBu+UaEV0EQWiypqamkpaX5/4Uqvh7OUUcdRZs2bdi+fTsAOTk5HDhwoMYYt9tNYWGhPyc2JyeHvLy8GmO07fqyZKuzfft2pkyZ4i+EAUwmE5MnT/bPoy6kHhVaAh6v4hdNk6xB+2eAqlqypTlfC7XYgRBFyi0Ht3DK/FO4Z/k92N12hnUdxh9Dn+Fv3zxPh/ItHFKSeL3L43De9KgIr1Dl5rWYDKQlhvb9IAiCEGsef/xxDAYDkyZN8r9mt9sZP348rVu3JiUlhdGjR9eqL3fv3s2IESNISkoiKyuLu+++G7c7ML0o1HozXHRRo0wmE6NGjWqRLoO0RHON3KXYOV9VoTLkzFd/7EDj3xJ/HfqLvWU7AHh141v8VfIXWclZPHLWI/x151/MGTGHozOPDmkeAMX+2AG1eEm1qddWGqrzVWu4FYXYgbwIOF/dXmm4BUD+dnhlCKybp26fNhmu/xTSj4jtvARBEJohe/bsoaCggHbt2gEwaNAgiouLWb9+vX/MF198gdfrZcCAAf4xq1atwuWq+nu9bNkyunfvTqtWrRo954knnsjWrVtrvb5161aOP/74RvdvyfWo0Pyp9K1Sg9DvN7SmW44W5HxVFIV8n1CZGWTsgNvrZvrX0zlh7gn8sPcH0hPSWTBiLp9l9qbtokngOERuWm/Od0xnY1LwhpNw0CIHWicnxKTfiCAIQrisXbuWuXPn0qdPnxqv33nnnSxatIh33nmHlStXsm/fPi655BL/+x6PhxEjRuB0Ovnuu+949dVXWbhwIVOnTg3ovOHWm6Eij8nCxGAwkJNuY8dBLfM1NuJruJmvmjvU1oDzdcP+DTy5+kne2vwWGfYpJDOYdslHcd/Qv3NVn6uwmfUJlC86LHYg3MzX6Dhf1WvPL3Pg9nh1jQhwuTXnawsWX39+Bz6ZBM4ySGoDl8yFo4fEelaCIAhNhrKyshpP83fu3MnGjRvJzMwkMzOThx56iNGjR5OTk8Mff/zBPffcw9FHH82wYcMAOPbYYznvvPMYN24cL774Ii6XiwkTJnDllVfSvn17AP7+97/z0EMPMXbsWO699142bdrEM888w1NPPVXvvH7++Wf//0+cOJE77riD7du3M3DgQADWrFnDnDlzePzxxyPxZRGEJkOFU62DDYbQe0xYWmDma5nD7XcMBxM78HPez4z5aIw/Um1EtxG8ctoD5Hx2H+zfqA46ZSKf2a5h7+Lfa4jj0UCLUmiTKs22BEGIPVoDWI2EhIQGV2OVlZVx1VVX8fLLL/Poo4/6Xz906BDz5s3jjTfe4OyzzwZgwYIFHHvssaxZs4aBAweydOlStmzZwvLly8nOzqZv37488sgj3HvvvUybNq1G41eNeKg3RXzVgXbVxNemm/lad8MtRVFYsn0JM1fP5IudX/hfz0nJoPQQTDz5Hsae2C3EWdfG61U4VKk6ZrTYgbRE9b/hZ75G7rNpnWzFZDTg8SrklznJSdevs6nL24JjB5wVsORe+PE1dfvI02D0K5DWLrbzEgRBaGKsW7eOs846y789efJkAK677jpeeOEFfv75Z1599VWKi4tp3749Q4cO5ZFHHqlROL/++utMmDCBc845B6PRyOjRo5k9e7b//fT0dJYuXcr48ePp168fbdq0YerUqdx00031zqtv374YDAYURfG/ds8999Qa9/e//50rrrgirK+BIDRlKp1VzbZCdTpqzteWlPmqxZklWU0BxTW4PC6mfzOdR1c9isvrIsOWwTPnPcM1phQM/70MnKWQmAkXvwjHDCPh+91A1b1UtMgvDS9KQRAEQU969uxZY/vBBx9k2rRp9Y4fP348I0aMYMiQITXE1/Xr1+NyuRgypMpo1aNHDzp16sTq1asZOHAgq1evpnfv3jWavA4bNoxbb72VzZs3c8IJJ9Q6XzzUmyK+6kC79Krc11g7X0tDjR3Q3KEWbTmSgzd+eYMnVz/J5oObATAZTFze63KmDJrCp+sTmf/tTsod+j7lLbG78K2yrxY7EK7zVYsdiJxz1Gg0kJWawP5DdvJK7PqKr54WGjtwcJua7XpgC2CAM+6B0+8Bk/zaEgQhMLxeL8XFxQGPz8jIwGhsnr9rzzzzzBoF5+F8/vnnjR4jMzOTN954o8Exffr04euvvw54Xjt37gx4rCC0ZDRnZVIY/SWsfudr/b8Lmhv5ZYFHDmzM3cj1H17PT3k/ATCy+0heGPY07b59BtbNVwd1GgSj50G62ujQ5r93iq7zNV9zvqaI+CoIQuwJpgHsm2++yY8//sjatWtrvZebm4vVaiUjI6PG69nZ2eTm5vrHVBdetfe19+oiHupNUTF0oF01oS3U7qPh4ne+hugO1Z7WuhU7j339GM/+8Cy5Zeo3boo1hZtOvIk7Bt5Bp/ROAKzc/BsA5SGKvfVR5Mt7Tbaa/E/n08LOfI187ABAVpqN/Yfs5JbY0SspxOtV8LTEzNeNb8CnU8BVAclZMPplOOrMWM9KEIQmRnFxMbM+2YAtObXRsfbyUiZfcAKZmZlRmJmgceSRR8Z6CoLQJKjwOV/DMXr4na+e6AqFsURzvrZuQKR0epw88s0jTP9mOm6vm9aJrXl2+LNc2a4/hjevhrxfAAMMngxn/qOGEUBb9WiPcuyA5nyV2AFBEOIBrQFsY/z111/ccccdLFu2DJtNP8NaY8RDvSniqw7UcL5GWOCrj5Qw3aFFlWUA3LVsIkUsA6BDagcmDpjITf1uIsOWUfN8CWqhEWrMQb3z8OW9aq5XgDTftZVUhtdMLJKxAwA5aQn8BBzQsemWFjkAYG4JsQPOcvj0LvjJ56zqcgZc8jKkZje8nyAIQj3YklNJTsuI9TSEANm3bx/ffPMNBw4cwOutuYx34sSJMZqVIMQeLXYgHOer9iDf6W45zteCMq0xVd0i5faK7Tww/wH/Sr/Rx45mzvlzyN6xEuaeAa5yX7+Bl+Doc2rtr4nhMct8ldgBQRCaEOvXr+fAgQOceOKJ/tc8Hg+rVq3iueee4/PPP8fpdFJcXFzD/ZqXl0dOTg4AOTk5/PDDDzWOm5eX538vEGJRb4r4qgPx4HxNTVDdocGKod/v+Z6Zq2ey5q8BJHAsdk8Zx7c/nrtOuYvLe12O1VR3oZKSoLlR9RVfi7VmW8kW/2upmvPVEarzVRNfIyuMa0238kocuh3TXW1ZmLW5O1/ztsA710H+b2Awwpn3w+ApYIzNz5QgCIIQXRYuXMjNN9+M1WqldevWNXItDQaDiK9Ci8af+RpAbml9aLWkswU13CrQnK+Hia92t50Hv3qQmb/NxIuXtkltmXP+HC7rNgI+uwc2/Ecd2HmwagSop9+AFmsW9czXMmm4JQhC0+Occ87hl19+qfHamDFj6NGjB/feey8dO3bEYrGwYsUKRo8eDcC2bdvYvXs3gwYNAmDQoEH8+9//5sCBA2RlZQGwbNky0tLSamXP1kWs6k0RX3Wger5nzBpu2bTYgcbFUK/iZdG2RcxcPZNvdn8DQI5yGgCPnTONO04/t9Eg/2Sf81X32IFyrdlWVSERfuZrzTzbSFElvurofK1WHJuNzdT5qihqQ63P7gG3HVLbqU21Op8W65kJgiAIUeRf//oXU6dO5f7772+22buCECoVLq3hVug/GxafEcHVghpuFZTVjh34fs/3jPloDFvztwJwec/Lee7852hbXgAvnw0Ht6L2G7hX7TnQgBHAFqPYAf91ifNVEIQmRGpqKscdd1yN15KTk2ndurX/9bFjxzJ58mQyMzNJS0vj9ttvZ9CgQQwcOBCAoUOH0rNnT6655hpmzJhBbm4u//znPxk/fnyDWbMasao346KynTNnDp07d8ZmszFgwIBaFuL6ePPNNzEYDIwaNSqyE2yE9nHQcMuf+ep04/XWvZSo0lXJi+tepMdzPRj11ii+2f0NFqOF6/teT9dWPQAY2LFfQB1UNUE0KrEDiarztaQyvDzbSMcOZKWqP+i5OoqvmjPBYABTcxRfHaXw/jhYNFEVXo8eArd8I8KrIAhCC6SiooIrr7wyZsJrU69HheZNpVOtuZPE+RoU2vL81slWKl2V3LPsHk6Zfwpb87eSnZzNfZ3v47+j/kvb35bCy2epwmtKNlz7EZx1f6MrsKoyX2PkfJWGW4IgNDOeeuopLrjgAkaPHs3pp59OTk4O77//vv99k8nEJ598gslkYtCgQVx99dVce+21PPzwwwEdP1b1ZszF17feeovJkyfz4IMP8uOPP3L88cczbNgwDhw40OB+u3bt4q677mLw4MFRmmn9pCWa/X94YyW+amKoolQ9Gdc4UH6AaV9No9PTnbj101v5vfB3MmwZ3H/a/eyatIsFIxegeFWBM9D5p4QYc9AYxRWa87V67IBOztcIxw5oDugDEYgdsBiNAYniTYm0ij8xzx8Cv7wDBhMMmQZ/fweS28R6aoIgCEIMGDt2LO+8805Mzt0c6lGheVMVOxBOwy21lnS1IPFVa7hV6PyTvnP78n/f/R9excvVfa5m47iNnJraF9PH4+Gj29RGr0edqRoBjjojoONr906OKDpfPV7Ff11tUiR2QBCEps1XX33F008/7d+22WzMmTOHwsJCysvLef/992tluR555JEsXryYiooKDh48yMyZMzGbA3s4Gat6M+axA7NmzWLcuHGMGTMGgBdffJFPP/2U+fPnc99999W5j8fj4aqrruKhhx7i66+/pri4OIozro3BYKBduo0d+eVhLQUKhwSzEbPRgNurUGZ3k5JgZlv+NmatnsWrP72Kw6MKgp0zOjNpwCTGnjiWFGuKf/9gc1GTo9hwy5/5GrL4GuXM11L9YwcszanZlqJgXD+f0397GIPigrQOcOl86DQw1jMTBEEQYsj06dO54IILWLJkCb1798ZisdR4f9asWRE7d3OoR4XmTVXsQBjiq7/hVssRXw/46vKHVt1Npek32qW0Y+4Fc7mw+4W49v7EGdsexOjYr/YbOOsfcNrkoPoN2Hz3ftFsuFVU4URb6JhZTyMxQRAEoW5iVW/GVHx1Op2sX7+e+++/3/+a0WhkyJAhrF69ut79Hn74YbKyshg7dixff/11g+dwOBw4HFVOxNLSUgBcLhcuV2jL2OsiJz2BHfnlJJgNuh43GFISzBRXulj++ze8+dvTfPr7p/73+rfrz+SBkxnVfRRmo/qxV5+nllNkNngDmr/NV5OU2fX9Ohb6ltCkJRj9x030ncvp8VJWYceIWjAGel5tmZbFGPg+oZDpm2hxhYuyCjsJOrigK31Nxsym2H1f6Yq9BNPiOzFt/QgAT9dz8V40B5IyoTlcXwtB+15sFt+TLZSW8hm6XC4UxYPX2/hNsaJ4/LVBtPcLheb42U2fPp3PP/+c7t27A9RqgBApolGPQvRqUiE6RPv3aJkvfssWxr2G1rvV7nS3iO+5r3d/zbYD+4EMPIZiru1zLf93zv/RypaB+4f5mJfeT6rbjjclB+/FL6F0OgU8XvVfgJh89yVur0Kl3YE5Cg1ydxwoAdSVgorXgyuAvznNlZZSzzRntM/O41Hivl4LZr/q+2r/H639olmTNsWfvVjVmzEVX/Pz8/F4PGRnZ9d4PTs7m19//bXOfb755hvmzZvHxo0bAzrH9OnTeeihh2q9vmrVKrZs2RL0nOujr9VAZWsD3r9+YnHuT7odN1A8isf3FDuRsYvG4zT+hgEDJ6WdxMiskfRM7olhp4GlO5fWuX+l0wQY+G7VSrYEEB1U5gIwU+nysujTxehlzNz+lxEw8udvW1hctBkArwIGTCgY+ODTz0nzPeBdtmxZQMfcs0895rYtm1ic/0uj40NFUcBiNOHyGnhr0ee0sTW+T2PsLQcw43W7WLx4cfgHjCEZFTvov/N5kp0H8GJiS4fL+SP1PPhqTaynJoRIoD+DQvzS3D/D0tJS/thrxJac2uhYe3kpy+x/kJqaGvX9QiE/Pz+k/eKZJ598kvnz53P99ddH9bzRqEchejWpEF2i9Xt0yy61nt3/158sXrwzpGPk7lWPsWnrrywu26rr/OKJSk8l/9n/HxYfXEwn74cYgAlHXs/pxt6sXf4Fx/+1gCOK1PozL7UPPx55E85NxbAp+FpbTYNQb6k/XrzEb1CJJG/tUD/HIxMdTf7+QC+aez3TEti1axe25IJGx8WyXgtmv+r7AlHdL5o1aVOsR2NVb8Y8diAYSktLueaaa3j55Zdp0yawXMj777+fyZMn+7f37t1Lz549Of300+ncubNuczsfuFO3owVOqaOUhT8tZPba2Tjdd2GlCzZjBtedMI6JJ0+ke+vujR7D41XwrFb/YJ03dEhAy1ccbi8PrFsOwBlnn+tvihUuL+xcDSWlnHXKSQzuVvUZT934BaV2NyefegYdM6wsW7aMc889t5ZFvC7ezFsHxYWcdGJfzu/TTpd51ses375md2ElPfsNov+RrcI+3qa9JfDzGlKSEjn//NN1mGEMUBSM617GuPzfGLwulPSOOC98kT82FwT8GQrxhcvlCupnUIg/WspnWFhYyM6vd5CUmtHo2IrSYs4dfBSZmZlR3y8Udu3aFdJ+8UxCQgKnnnpqrKfRKKHUoxC9mlSIDtH+Pbr64y2wfw+9enTj/LO6hnSM9Z/+yrd5u+ly1NGcf243nWcYH3y560vuXHwnO4t3YiQZg+9296G/3U1C/mbMH4zFULQDxWDCdfp9rDnUjXOHDgv5M/R6Fe7+Qb2POuOsc2gd4QZYpXY3969fCXi4a+TJDOgS2t+Q5kJLqWeaMy6Xi/fff5/OnTuTmtH4/XMs67Vg9qu+LxDV/aJZkzbFejRW9WZMxdc2bdpgMpnIy8ur8XpeXl6tQF2AP/74g127dnHhhRf6X/N61aUeZrOZbdu20bVrzWIkISGBhISqP4IlJeoyDYvF0qR/Qe8t2cuzPzzL3PVzKbYXA3CEyQlueGnEa1zRv3HRVcPlrMpSTU1KwGJp/NvCYlFzo5weL3avgdY6fS0P+ZZUtUlLrPH5pNkslNrdVHrwvx7oZ+j0Na1Kslkj/pnnpCWyu7CSggq3LufyGtSlSxaTsWl+v1YWwUcT4NdP1O0eF2AY+RwmcwpsXtzkfw5bOvL5NX2a+2dosVgwGEwYA8jvMxhM/q9HtPcLheb4ud1xxx08++yzzJ49O6rnjUY9Cs23Jm3pROvzc7jVejbFFvr5Eq1qje/B0Oy+50ocJdyz7B7mrp8LQKf0Tjw6+GX+9Y6L1AQTKZv+A0v+AR4HpB2B4dL5GNqdCIvDr0cTzEYcbi8uJfL1+ifr9lLh9HB0Vgqndstqdg15Q0V+jzZ9TCZD3NdrwexXfV/t/6O1XzRr0qb4cxerejOm4qvVaqVfv36sWLGCUaNGAWrxumLFCiZMmFBrfI8ePfjll5rLxv/5z39SWlrKM888Q8eOHaMx7ZjyS94vPLn6Sd745Q1cXlWo7JbZjSmDpvDdz8ez8rcCDCQFdUy7qyrXyGYOfK1Mis1MYbmTch2bbmkNt1ol1XTfptrUb9WSyuAzRRxuNeck0g23ALLS1JuqvBJHIyMDw92UG27tWQfvjIFDu8FogaGPwoCbwWCQfFdBEAShFj/88ANffPEFn3zyCb169apV0L///vsROa/Uo0JToMJnltAE1FCwNNOGW0v/WMq4RePYfWg3ALf2v5UnhjzBr/tdpLKC2eb58Ol36uBjhsOo53XtN2CzmHC4vf57jkihKAr/XfMnAFcN6CTCqyAIQgjEqt6MeezA5MmTue666+jfvz8nn3wyTz/9NOXl5f5us9deey0dOnRg+vTp2Gw2jjvuuBr7Z2RkANR6vTmhKArLdyxn5uqZLP2jKrN1cKfB3HXKXVxwzAUYDUY2/74BUJejBIPWbMtqMmI0Bv5HPDnBRGF58OdraB6aEJyRVPMHIM2mbodyLofvmAlBCMuhkpOmBr3mldh1OZ7L59q1RCG8XzcUBVY/B8ungdcNrTrDpQugw4mxnpkgCIIQx2RkZHDJJZfE5NxSjwrxTqWvnk0Ko6Gr1WdEcAbRUCqeOWQ/xJSlU5i3YR4AXTK6MO+ieZzV5SwAXLuX8Yn1HxzpOQBGM5z7MAy8TTUC6IjNYuRQZU1DSyRYu6uI3/LKSLSYuOTEIyJ6LkEQhOZKrOrNmIuvV1xxBQcPHmTq1Knk5ubSt29flixZ4m96sHv3bozGJiQ86YjT4+TNTW/y5Oon+TnvZwCMBiOX9ryUKYOmcHKHk2uMT/G5Q8uCFCgdbk2cDO7rnJJgASop08n5qrlezUYDKQk1vzU152upPRTnq+/6LJH/PsrWW3z1as7XJvIzUFEIH94Kvy1Rt3uOgotmgy09ptMSBEEQ4p8FCxbE7NxSjwrxTqXf+Rq6+NqcnK+Lf1/MTYtuYm/pXgBuP/l2HjvnMVKsKaoR4Pu5DPjyAUxGN/nmHNpc/wYc0S8ic0n0CeKaoSVS/Mfneh3Ztz3pOvXbEARBaGnEqt6MufgKMGHChDqXdQF89dVXDe67cOFC/ScUY4rtxby0/iWe+f4Z9pXuAyDZkszYE8YyaeAkurTqUud+qT7BsswRnECpFQoJQT5JT0lQx+sVO1BUrs47I8laaxmN1tCrJCTxNRaxAzqJr77i2NwUYgd2r4F3x0LJHjAlwHmPQf+xursLBEEQBCESSD0qxDMVTrWeDUd81ZyvribsfC2qLOLOz+/k1Z9eBeDozKOZf9F8Bh85WB1Qrd+ACVjiOYk1PR9iWoSEV1BjBwAqIyi+Hix1sGTTfgCuHnhkxM4jCIIgRIa4EF8FlT+L/+TpNU/zyoZXKHOWAdAupR0TB0zk5n430yqx4e5/KX7xNbTYAVuQzlD/+XSKHSj2573WfpJb5XwN/lz2KMYOVDlf9cl8bRKxA14vfPs0fPEoKB7I7AqXLYR2fWI9M0EQBKEJ0aVLlwYzDHfs2BHF2QhCfKEJe2HFDvge5jdV5+vH2z7mlk9uYX/ZfgwYuHPgnTxy9iMkWXz9Lqr3GzBZWdxuArdt78f49NYRnVeC3/kaua/r2+v+wuVROL5jBsd1kBVlgiAIoRKrelPE1zhg3b51PLn6Sd7Z/A4eRS2sjss6jrsG3cWVx11JgjmhkSOopIQoUFaJk0GKr1oOq26xA6qr9fBmWxCe+BpN52v1zFdFUcIOwnd747zhVnk+fHAzbF+ubve+DC54ChJSYzsvQRAEockxadKkGtsul4sNGzawZMkS7r777thMShDihMoW7HwtqCjgjiV38PovrwPQvXV35o+czykdT1EHeL2wZk61fgNd4LIFLP5KAfaTmRzYvVSo2Hxf10jFDni8Cm98rzYTu0Zcr4IgCGERq3pTxNcY4VW8LP59MTO/m8nKP1f6Xx9y1BDuGnQXQ7sODVq4C9X5qomTtljHDvicr4c324KqhlsllcHFDiiK4s98Dfb6QkGLHahweihzuEm1hZfHpDkT4tL5uusbeO9GKN0PZhuc/39wwjUSMyAIgiCExB133FHn63PmzGHdunVRno0gxBda7ECSDpmvjibkfH1/6/vc9ult5JXnYTQYuWvQXUw7cxqJlkR1QEUhfHAL/P65ut3rYrjwGbClU1i+BoA2KbWNHXqiCeKREl+/2naAvcWVpCdauKBPu4icQxAEoaUQq3ozDhWd5o3dbefl9S/T6/leXPi/C1n550rMRjPX9LmGDTdvYNk1yxh29LCQHJOpITbc0pyvwYuvoYm99VEVO1CX81XLfA3uXC6PgqKu3I9Kw60kq9n/OegRPeD2qpM3x1OTD68HVs6AVy9Uhdc2x8C4L+HEa0V4FQRBEHRn+PDhvPfee7GehiDEFC12INEaundGE1+bgvP1YPlBrnj3Cka/PZq88jx6tu3Jdzd8xxPnPlElvO5eAy+epgqvpgQYMQsuXeBv9FpQpt5btI6489UnvkZI1P6vr9HWZf2OiIqZRBAEoSUS6XpTnK9RIr8inxfWvsBza5/jQPkBANIS0ri5381MHDCRI9KOCPscKQmqQBm68zXYzNfQzlcfhVrDreSGMl+Dc75q1wbRiR0ANfe11F5GXomdo7NSwjqWVhxbzXEiapbmwfvjYKfPrX3832HETLAmx3ZegiAIQrPl3XffJTMzM9bTEISY4fEq/tVQYWW++mrheM58VRSFtze/zYTPJpBfkY/JYOLeU+9l6hlTq6LYDu830Ppotd9ATu8axyooV40QmcmRdb5q91B2p/7O178KK/jqt4MAXCWRA4IgCBEj0vWmiK8R5veC33lqzVMs3LiQSnclAB3TOnLHgDsY128caQlpup0r1MxXR4gNqZJ9sQP6N9yqXSClJYbmfK2+rMoapaX7OWk2th9Qxddw0RpuxYXzdcdX8N44KD8AliQY8ST0/XusZyUIgiA0E0444YQaK38URSE3N5eDBw/y/PPPx3BmghBbKpxV9W9Yma9+56sS9pwiQV5ZHrctvo33t74PQO+s3iwYuYB+7ftVDSo7qPYb+GOFut37crhgVq1+A16vQmG5em8R6dgBmyVysQOvf78bRYHB3drQpY2YHQRBEMIlVvWmiK8RQFEUvvvrO2aunslHv36EglrgnNjuRO4adBeX9rwUiym8LNC68McOBOlEtYfofA31fPVR5Bdf9XS+VjUTC7f5VaBoua96xA5ozteYZr56PbDyCTVqAAWyeqpLurJ6xG5OgiAIQrNj1KhRNbaNRiNt27blzDPPpEcP+ZsjtFy0ZlsGQ3grueLV+aooCm/88gYTl0yksLIQs9HMA4Mf4B+D/4HVVE043fUNvDsWynLBnAjnz6i330BxpQtfehetIu581WIH9BVfHW4Pb6/7C4CrBojrVRAEQQ9iVW+K+KojHq+HD3/9kJmrZ7Jmzxr/6yO6jWDKoCmc2fnMiAqAqdUyWBVFCfhc2lNaW9DOV73FV1/sQF3O15Bdveq1RStyANTYAUAX56s71rEDJfvVplp/fqNun3gtnPcEWJNiMx9BEASh2fLggw/GegqCEJdoea9JFlNY9xLxmPm6r3Qft3xyC4t+WwRA35y+LBi5gL45fasGeT3w9ZPw1XRQvNCmuxozkN2z3uMW+iIH0hMtETcxVDlf9f26LtmUS2G5k5w0G0OOzdL12IIgCC2VWNWbIr7qQLmznAUbF/DUmqfYUbQDAKvJyjV9rmHyoMn0bFt/YaAnWuyAx6tQ6fKQFGAgv1YoBNuQyt9wKxqxA76GW6V2F4oS+FIpv/M1iuH0OTqKr85Yxg5sXw7v3wwV+WBNgQuehj6XRX8egiAIgiAILZgKp9ZsK7x6VnO+OuLA+aooCq/99BqTPp9Esb0Yi9HC1DOmcu+p99ZcIXh4v4G+V8H5/9dov4F8rdlWhCMHoGr1YKXOsQP/Wa022vrbyZ0wx3IVnCAIghA2Ir6Gwf7S/Tz3w3O8sO4FiuxFAGQmZnJr/1uZcPIEclJyojqfRIsJowG8iiqIBiq+ak2pgs181T92QHW+1h07oL7mVaA8iDD76rED0SLbHzugn/M1qrEDHjd8+Sh885S6nd1bdRe0OTp6cxAEQRBaDEZj49FABoMBt1ufekMQmhp6ia8Wk/pzFmvn656SPdy06CY+2/4ZAP3b92fByAUcl3VczYG1+g3Mgr5/C+gcBZr4GuHIAYhM5uuvuSWs+7MIk9HAlSd31O24giAILZVY15sivobA5gObmbV6Fv/95b84Peof9q6tujJ50GSuO/46kmPU+d1gMJCSYKbE7qbU4SbQxSma89UWpDtUix0o10F89XgVSuz1xw7YLEbMRgNurxJU9EAsYgey/M5XPTNfoxQ7cGiPmqX1ly82o/9YGPYYWGzROb8gCILQ4vjggw/qfW/16tXMnj0brzf2Tj1BiBV2f+xAeLduWj3sjJH4qigK8zbMY8rSKZQ4SkgwJfDQmQ8x5ZQpmI3Vrs3jVvsNrPo//P0GLnsV2h4T8Lm02IHWyQk6X0VtbJqjWMfYgf+uUV2vQ3tm+yPNBEEQhNCJdb0p4muAKIrCl7u+ZOZ3M/1PaQEGHTGIu065i5HdR2IyRm9pe32k2iyU2N1BRQH4M19DjB0o1UF8PVTpQksTyKjD+WowGEi1mSmqcAV3bX7na/Q+G61AOlBqDyp7ty60brRRcb7+9rnaPbayCBLS4MJn4LhLIn9eQRAEoUUzcuTIWq9t27aN++67j0WLFnHVVVfx8MMPx2BmghAfaM5XW9jOV1/mawxiB/4s/pNxi8axbMcyAAYeMZD5F83n2LbH1hxYsh/eGwt/fqtun3gdDH8CLIlBnU+LHciMQuyA5kjWy/la5nDzwY97AbhmoDTaEgRB0INY15sivjaCy+Pi7c1v8+TqJ9mQuwEAAwYuPvZipgyawikdT4nxDGuSEkITLEeIAmVqgiqSOt1enG6vP0cqFIp8ea+pCeZ6hca0RAtFFS6/QzYQ/M7XIIXlcMhKVZ+wuzwKheVOWqeE/sRdc76aI+l89bhg+TRY/Zy63a4vXLYAMo+K3DkFQRAEoQ727dvHgw8+yKuvvsqwYcPYuHEjxx13XOM7CkIzpsKp1vVJYfYwsMbA+epVvMxdN5d7lt9DmbMMm9nGo2c9yqSBk2obV35fDh/cBBUFar+BC5+B3peGdN7CcvXeok0UYwf0ynz9YMNeyp0ejmqbzKCurXU5piAIglBFLOpNEV/rocRRwsvrX+bp759mT8keABLNidxwwg1MGjiJozPjM/9Sa7oVzNL8UJ2vyQlVBVO5w43VHHpxozXbykiu7XrV0DJmg3HaasKyLYrOV4vJSJsUK/llTvJKHLqIrxFzvhb9Ce/eAHvXqdsDboFzHwZz5JdoCYIgCILGoUOHeOyxx3j22Wfp27cvK1asYPDgwbGeliDEBf7YAb2crx4l7NVZgbCjaAc3fnwjX+76EoDTOp3GvIvmcUzrw+IDDu83kNMbLl0YVr+BAi12IIw6PFA0A4sezldFUXjdFzlw1YAjI/4ZCYIgtCRiWW+K+HoYfx36i9nfz+alH1+ixFECQFZyFreffDu39r+V1knx/fQxFOdrqJmvZpMRm8WI3eWlzOGmVRhPlovKtWZb9R9Dc9qW2t0EOlO/qzeKzleArFSbKr6W2ulJWsjHcftjByJQeG39BD66DeyHwJYOI+fAsRfqfx5BEARBaIAZM2bwxBNPkJOTw//+9786l4UJQktGr4Zb1VepOT3eiMVyeRUvc36Yw30r7qPCVUGiOZHHhzzOhJMnYDQcVpMf3m/gpBth6L/D7jfgjx2IivNVvSa7Dpmv6/8s4tfcUmwWI5eeeETYxxMEQRBUYl1vivjqY8P+DTy5+kne2vwWbq8qXB7b5limDJrCVX2uwmZuGkHnmvO1LJil+e7Qm1KlJJixu5xBib11ocUO1NVsSyMtUb22ErubVgEeN5xrC4fstAS27Ie8Q/awjuOMhPPV7YBlD8L3L6jbHfrBpQuglWRKCYIgCNHnvvvuIzExkaOPPppXX32VV199tc5x77//fpRnJgjxgV98DTd2oFo96fIoJETgTvD3gt8Z+/FYvt79NQBnHHkG8y6aR9fMrrUHb1sCH95S1W/gotnQ62Jd5qHFDrSORuar73Oxu8N3vv7H53q96Pj2pNfRB0MQBEEIjVjXmy1afFUUhSXbl/Dk6idZsXOF//WzOp/FlEFTGN5teO2ns3FOaiiZryE6X0EVX/PLwhdfiytUsTizgSIj1aa+VxaM+OqKfsMtgJx0VazPK3GEdRzN+WrWS3wt3AnvXA/7N6rbgybAOQ9CGJERgiAIghAO1157rSytFYQG0Dt2ANSeDei4It/j9TD7+9k88MUDVLorSbYkM+PcGdzS/5ba91NuJ6x4qKrfQPsTVCNAZhfd5lNQ5osdSI587IB2D2V3hie+FpQ5+OyXXACulkZbgiAIuhLrerNFi68zvp3BfSvuA8BkMHF5r8uZMmgK/dr3i/HMQieUXFTtKW2wma9Q3Wkbeedragh5tlXNxKIfOwCQVxqe81XLfLXqETuw+UP4+HZwlEBiKxj1AnQfHv5xBUEQBCEMFi5cGOspCEJcUxU7EN6tm8lowGQ04PEq/hpTD7blb2PMR2NYvWc1AGd3OZtXLnyFLq3qEFNr9Ru4Fc59SNd+A26Pl+JK1dgRDeerX3x1h/c1fXvdHpweL32OSKfPERk6zEwQBEHQiHW92aLF17/3/jszvpvB9cdfzx0D76BTeqdYTylsUhKq3KGB4m+4FYI7NNkavNO2LooqGs98TfM5X0vsroC/c/2xA1HOfM1OU8XXAyVhiq9eLfM1jPm77LD0AVj7irrdcQBcOh/SJUdKEARBEAQh3tErdgDU6IFKr0d1voaJx+th1upZ/OvLf+HwOEi1pjJz6EzGnTiubndRrX4Dz8OxF4Q9j8MpqnChKGAwNHxvoRdVma+hO189XoXXv1cjB8T1KgiC0Pxo0eJrx/SO7Ju8j4Rm1Nk9JRx3aAgCpeZGDT92QHW+tkpuKHag2rWlBHbcKudrdGMHstPU76nccMVX3/xDjh0o+APeuQ5yf1G3T7sTznoATJIhJQiCIAiC0BSodKp1drixA6A2ca10VfUVCJUtB7cw5qMx/LD3BwCGdR3GSxe+VLeZxe2AZVPh+xfV7Q794bIFkBEZ40tBuRo50CrJiskY+SWm/sxXl4clm/aHdIw/Dpazp6iSNJuZC/u013N6giAIQhzQosVXoFkJrxBa5qv2lDYUgTLFd77yaDTc8jlfSx1BiK+u2MQOaM7XsDNfvWHEDvzyLiy6A5xlkNQaLn4Jug0Jaz6CIAiCIAhCdKl0abEDOjhfzSbAHbLz1e11M+PbGTy08iGcHifpCenMGjaLMX3H1O12LdwB74yp6jdwyu1qv4EIGgEKy3zNtpKj09NA+1y8Ctzy3x/DOtal/Trq8jkLgiAI8UWLF1+bG6FksNrDaLiVnBC807Yuiv2xA/UXYmmJwZ9Ly7ONvvNVFV/zyxy4Pd6QnatOreGWMYj9XZXw2T3w42vq9pGnwuhXIE2eoguCIAiCIDQ19I0dUAXSUDJff8n7hTEfjWH9/vUAjOg2grkXzKVDWoe6d9j8AXw8sarfwMVz4ZhhIc89UPLLVfE1M0ria6rNwsSzj+a7PwrCOk5GkoVbzjhKp1kJgiAI8YSIr80MzYkaTMMtfy5qCO7QFJ1iBzTna0O5TKma89XuCvi4fudrlDNfWydb/Q0N8suc5KTbQjqOFjtgCfSzObgN3rkeDmwBDHD63XDGvWCSH3VBEARBEISmSKVPfNUjdsDqqymDcb66PC6mfzOdR1c9isvrIsOWwTPnPcM1fa6p2+3qssPn/4B189TtjgPh0nlR6zdQWKauPGuTEr0VjpOHdmdy1M4mCIIgNDVEkWlmVImhgQmUiqKE5XxNsYYfO6Aoir/hVkYDztfUkPJstWZi0RVfjUYDWakJ7D9kJ7fEHrL4qsUOWALJq9r4P/h0MrgqIDkLLnkJup4V0nkFQRAEQRCE+EDP2AGtiWugma8b9m9gzEdj+CnvJwBGdh/JCyNeoF1qu7p3yN+uGgHytH4Dk339BqJ321ngc762TomO81UQBEEQGkPE12aGP/M1QIHSUe2pty0Ed6i/wVcY4mulq6rjakPO1xqZrwFS1Uws+tlJ2Wk29h+ykxdG0y2XL3agQeersxwW3w0bX1e3u5wOl7wCqdkhn1cQBEEQBEGIDyr1jB3w1ZRajVkfTo+TR1c9yvRvpuP2ummd2Jpnhz/LlcddWbfbFeDnd+CTSb5+A23gkrlwdPT7DeSXRTd2QBAEQRAaQ8TXZkb1GABFUeovjnxoy/IhROdrkGJvXWiuV6vJ2OByKs35Wu7w4G24XvTjF1+j7HwFyE5TlzodCEt8Vedvrs/5mrdFdRfkbwODEc68HwZPAaME9QuCIAiCIDQHKvyxA+Hfuvmdrw3EDqzbt44xH41h04FNAIw+djRzzp9Ddko9D/adFbDk3mr9Bk7z9Ruoxx0bYQrL1diB1lGMHRAEQRCEhhDxtZmhiaEuj4LD7W1UUNWW5RsNDQh8AZwvnNiBIt/SoIwkS4NisZb5CmD3BHZshys2DbegqulWrg7iq+Xwhl2KAhv+A4vvAXclpOSoRW6XwSGfSxAEQRAEQYg/9IwdsJo052tt8dXutvPwyoeZ8e0MPIqHtkltmXP+HC7rdVn9Bzy838AZ98Dp98S030CBz/naWpyvgiAIQpwg4mszI9lqxmBQtbkyh7tR8bV63mtjLtm60KPhViDNtkBdJpVgNuJwe6kM8HSxdb6q4mteiSPkY7i12IHq4qujFD6ZDL+8rW53PRsufglS2oZ8HkEQBEEQBCE+iUbDre/3fM+Yj8awNX8rAFcedyWzz5tN2+QG6suNb8CnU6r6DYx+GY46M+w5hkthuYivgiAIQnwh4mszw2g0kGI1U+pwU2Z3N9rl0641pAoxQ0pzvgbTBOtwAmm2pZGWaOFgqYPKQJ2v/szXWIqvoTtfnX7nq08Yz/1FdRcUbAeDCc7+J5w6CYzRvz5BEARBEAQhsrg9Xn89qEfmq1ZTasesdFUy9cupzFozC6/iJTs5mxdGvMDFx15c/0Gc5fDpXfDTG+p2lzPgkpfjpt9AfpnEDghCLPB6vRQXFwc8PiMjI2JzEYR4Q8TXZkiKzSe+BuBG1TJfQ3WG+mMHnKGLr8UBOl9BzX09WOogUK1Xi1WITeyAlvmqg/PVaIC182DJ/eBxQFoHGD0Pjhyky1wFQRAEQRCE+KPCVeU40CV2oJrz9bu/vmPMR2P4reA3AK7uczVPD3ua1kmt6z9A3hZ45zrI/83Xb+AfMHhy3PQbcLq9lPhuFMT5KgjRpbi4mFmfbMCWnNroWHt5KZMvOIHU1MbHCkJzQMTXZogmiJbYXY2ODdv5aqtquBVIg6+6KCpX59kquXHnq5b7WukJ7DzhisvhoFfmawoVtPn8FvjtY/XFbsPg4hchKVOPaQqCIAiCIAhxit1Z1Z9Bj3pWi7J6e9N7fPL5XSgotE9tz9wL5nLBMRfUv6OiqA21PrsH3HZIbaf2G+h8Wthz0hMtzsxkNJCe2Pi9hSAI+mJLTiU5LSPW0xCEuEPE12ZIdUG0Mez+hlShFXPJPqHX7Q2swVddaEVSRgDO1zTftTWl2IFDlS7sLk/QXxtFUeih/MFz1mdJ/C0PjGYYMg0GjpeYAUEQBEEQhBZAhU98TQyxP8PhFNkPArBy17coFoXr+17PrKGzaJXYqv6dHKXwyZ3wyzvq9tFD4OK5kNwm7PnojRY50CrJijGEZsKCIAiCEAlEfG2GaM7XQGIHqjfcCoVka9W3UCANvuqiKnYggMxXn/M14NgBV+xiB9JsZmwWI3aXlwMlDjq1Tgp8Z0XBs2Yu71mnkWBw403riPGyBdDxpMhNWBAEQRAEQYgr/OKrNbzbtjJnGfctv48lfxhJZRjpCa1588rFDO82vOEd9/8M746p6jdwzr/glDvi1gigNdtqkyKRA4IgCEL8EJ9/NYWwSLUFLr5WZaKG9q1gMhpI9uVPBeK0rYuqhluBZb5CCM7XGMQOGAyGqqZbpUFED1QWwVtXY/78XhIMbj739McxdqUIr4IgCIIgCC2MSp+RICmMvNcvdn5B7xd6M2ftHBTUuvuWfhMaFl4VBda+Aq8MUYXXtA4wZjGcdmfcCq8ABWWq+NpaxFdBEAQhjhDnazNEc76WBhQ7EJ7zFdTogXKnJyCxty6CabiV5stuqnQ3vozI61X8nVzDub5wyE618WdBBbmHAhRf96yHd6+H4t0oRgsPOf7GQs8wfk9pYCmYIAiCIAiC0CyprBY7ECwljhLuWXYPc9fPBaBTeifObXMRyzd5MRoaqLvth2DRHbD5A3X7mPNg1AtNot9Agc/5mpmcEOOZCIIgCEIV8fvYUgiZlARVoAwsdkBruBX6t0JKEE7butCcr4HEDqT6hGV7AM5XTXiF2DhfAbLTfc7XxppuKQp89xzMHwrFu6FVZ4r/9ikLPecBBsySWSUIgiCEwapVq7jwwgtp3749BoOBDz/8sMb7iqIwdepU2rVrR2JiIkOGDOH333+vMaawsJCrrrqKtLQ0MjIyGDt2LGVlZTXG/PzzzwwePBibzUbHjh2ZMWNGpC9NEJo1FU61vk4M0vm69I+lHPf8cX7h9db+t7Lp1k10a9MFAKfbW/eO+zbA3NNV4dVohqH/hr+92SSEV4ACX+Zr62RxvgqCIAjxg4ivzZBgGm5VLcsP3RmqCaKhxw4E3nArmNgBhysOxNdU9an7gVJH/YMqCuF/f4OlD4DXDT1Hws2rsGf1AcBiMujSYEEQBEFouZSXl3P88cczZ86cOt+fMWMGs2fP5sUXX+T7778nOTmZYcOGYbdXPTy86qqr2Lx5M8uWLeOTTz5h1apV3HTTTf73S0pKGDp0KEceeSTr16/n//7v/5g2bRovvfRSxK9PEJorwcYOHLIf4saPb2TYf4fxV8lfdMnowhfXfsHzI54nNSEVi0mtiV2ew8RXRYHv58K8oVC0C9I7wQ2fwykToAnVof7YARFfBUEQhDhCYgeaIalBNdwK3/ma7DtfuTN48dXt8frjETIDKJK02IFAdF4tz9ZkNGA2xUh8TWvE+br7e3j3BijZA6YEOO8x6D8WDAZc5RUA/iJZEARBEEJl+PDhDB9ed76joig8/fTT/POf/2TkyJEAvPbaa2RnZ/Phhx9y5ZVXsnXrVpYsWcLatWvp378/AM8++yznn38+M2fOpH379rz++us4nU7mz5+P1WqlV69ebNy4kVmzZtUQaQVBCBwtdiAQ8XXx74u5adFN7C3diwEDt598O4+d8xjJ1mT/GM2QUMP5WlkEH02AXz9Rt3tcACOfg8SmF3ulxQ60TpHYAUEQBCF+EFWnGaI5XwPJfHX4xdfQna/BZMweTnGlGjlgMEB6YgCxAzZf5qun8SfwsWy2pZGVphZ+tTJfvV745ilYMFwVXjO7wo3L4aQb/e4Cl1edv0QOCIIgCPVRWlpKSUmJ/5/D0cBKi3rYuXMnubm5DBkyxP9aeno6AwYMYPXq1QCsXr2ajIwMv/AKMGTIEIxGI99//71/zOmnn47VWvUwddiwYWzbto2ioqJQL1EQWjQVzsZr9aLKIq778DpGvDGCvaV7OTrzaFZev5Jnhj9TQ3gFdUUVVHO+7lmnxgz8+gmYrDB8Blzx3yYpvAIUlPtiB6ThliAIghBHiPjaDEn1Z7C6Gh1rd4ffkEoTe8tDyHzVmm2l2SyYAhAZ/bEDQThfYym+5vicrzViB8rz4Y3LYfk0UDxw3KVw80po16fGvlpRbI3h/AVBEIT4pmfPnqSnp/v/TZ8+Pehj5ObmApCdnV3j9ezsbP97ubm5ZGVl1XjfbDaTmZlZY0xdx6h+DkEQgqOx2IGPt31Mz+d78tpPr2HAwOSBk/nplp8YfOTgOsdbfSuqHG4PfPcszB/m7zfA2KUw4OYmFTNwOIXlEjsgCIIgxB8SO9AMSQkidkBzvoYjUAZzvsMJptkWVImvgTTcsrvCz7MNl+qxA4qiYPjzO3hvLJTuB7NNdReceG2dRa7bowASOyAIgiDUz5YtW+jQoYN/OyFBltoKQnOiKnag5m1bQUUBE5dM5I1f3gCge+vuLBi5gEEdBzV4PIvZSAal3LR3Nvy+Rn2x5yi4aDbY0nWff7TxZ75K7IAgCIIQR4j42gxJDSJ2QBMoYxU7UFQeeLMtUB2yEKjz1Se+hpFnGy6a+Gp3unB88QS2b54AxQttjoHLFkJ2r3r3dfqcr2ZT03UfCIIgCJElNTWVtLS0sI6Rk5MDQF5eHu3atfO/npeXR9++ff1jDhw4UGM/t9tNYWGhf/+cnBzy8vJqjNG2tTGCIARHXbED7215j9sW38aB8gMYDUbuGnQX086cRqIlsdHjtTu0kU8T/kGHigJfv4Hp0P+GJu121bC7PH4zSCC9JARBEAQhWoilrhmSkqAKlGWBiK86LM33N9wKKXYgOOerJr66FEPNRgF1EA+xA4lWE51tZbxqeRzb19NV4fX4v8G4LxsUXkGcr4IgCEJ06NKlCzk5OaxYscL/WklJCd9//z2DBqkuukGDBlFcXMz69ev9Y7744gu8Xi8DBgzwj1m1ahUuV1Xs0bJly+jevTutWjXN/EhBiDWVLrW+TrKaOFB+gMvfuZxL37mUA+UH6Nm2J6vHruaJc59oXHj1euHrWZy5egwdDAXsN3fw9RsY2yyEV6iKHLCYDKTZxGMkCIIgxA+i6jRD/A23Aood0NyhoTtfqzJmQ4kdUIukVgE6X1OqFVKNXZ8jDmIH2LGS9w33MNi0CY8pEUY+Dxe/CAkpje6qZb5ajPJjKgiCIIRHWVkZGzduZOPGjYDaZGvjxo3s3r0bg8HApEmTePTRR/n444/55ZdfuPbaa2nfvj2jRo0C4Nhjj+W8885j3Lhx/PDDD3z77bdMmDCBK6+8kvbt2wPw97//HavVytixY9m8eTNvvfUWzzzzDJMnT47RVQtC00eLHdhW8Au9nu/FO1vewWQw8cDgB/jxph85ucPJjR+kPB/euAxWPIRR8fCh5xTuyZxdq99AU8cfOZCcgKGZCMqCIAhC80AeCTZDtBgAp9uLw+1pUHzUnK+2GGe+Bho7YDIaSE4wUe7wUGp30dAixpg6X70eWPkErJxBJgrbvEew+6w5nHvCmQEfQosdsJileBQEQRDCY926dZx11ln+bU0Qve6661i4cCH33HMP5eXl3HTTTRQXF3PaaaexZMkSbDabf5/XX3+dCRMmcM4552A0Ghk9ejSzZ8/2v5+ens7SpUsZP348/fr1o02bNkydOpWbbropehcqCM2MosoKAF775RXKzPn0zurNgpEL6Ne+X2AH2PVtjX4DW/r+i0nfdOZ4pfGIgqZGQbna4FYiBwRBEIR4Q8TXZogmhgKUOxoRX121c6SCJTkM8bXY73wNLHYAIDXB7BNfG3G+usPPsw2Jkv3w/jjY9TUAazJGcH3upUxUjuDcIA6jxQ6YxfkqCIIghMmZZ56Joij1vm8wGHj44Yd5+OGH6x2TmZnJG2+80eB5+vTpw9dffx3yPAVBUFEUhTd+eYMVf/yFmd4YDC4ePONB/jH4H1hNAYiLXg98PQu+eqxav4FXyT/UFr75odH4rqZIVbMtEV8FQRCE+ELE12aIyWggyWqiwumhzO5u8OmvHg23UjXxNZSGWz7xNSOIJ9SpNjO5JY7GxVd/7EAUxcvtK+D9m6AiHyzJcOHTrNrXB3vuHxwocQR1KC12wCqZr4IgCIIgCC2GfaX7uOWTW1j02yKyvU9gBmYMfYRbThsY2AHKDsB7N8LOler28X+HETPBmoylrACoqjObE5rztbU4XwVBEIQ4Q8TXZkpKgpkKp4dSh6vBcZo7NByBUsthDaXhVlGQDbegqulWSaPOV1/sgCUK4qXHDV/+G76ZpW5n94bLFkKbo8ku2wVAXok9qENqRbHZJLEDgiAIzRmv10txcXHQ+wiC0LxQFIXXfnqNSZ9PothejMVooUNKFwpK4NisroEdZMdX8N44KD8AliQY8ST0/bv/bauv5m+WztdyzfmaEOOZCIIgCEJNRHxtpqTYzBwodTTqRnXoGDsQSIOvwykOsuEWVGsoFmDsQMQbbh3aq2Zp7V6tbve/AYY9Br6us9lpagEYvPiqLg+1iPNVEAShWVNcXMysTzZgS04NaLy9vJTRvTMjPCtBEKLJnpI93LToJj7b/hkA/dv3Z8HIBdz+Wj4FlJPYWK1erd8AKJDVUzUCtO1eY5i2oqpZOl8ldkAQBEGIU0R8baakBpjDWpX5GrrAp52r3OFGUZSguotWNdwKLvMVGr82PVy9jfLbUvjgZqgsBGsqXDQbjrukxpCsNLVZSV6QsQNureGWOF8FQRCaPbbkVJLTMmI9DUEQooyiKMzbMI8pS6dQ4ighwZTAtDOncdcpd2E2mql0rgAgydqA+HpYvwFOvBbOewKsSbWGao1cm6PztVBzvkrsgCAIghBniPjaTEn1Lc0PXKAM3/nqVaDS5SHJGti3laIoITlf0xLV45dUNhKp4BOWIyK+elyw4mH4ztflud3xqrsg86haQ3N84uuBUjter4LRGJiY6vKLr+J8FQRBEARBaG78Wfwn4xaNY9mOZQAMPGIg8y+az7Ftj/WPqXCqtXxifeLr9uXw/s1qvwFrClzwNPS5rN5zas5XZ7N0vmqZrxI7IAiCIMQXIr42U1ISAluar4fzNclqwmAARVGbbgUqvpY53P6l9cGIr6kJqrDcWMyBX1gOI1KhTop3w7s3wJ616vbJN8PQR8Bcd6HXNlV93eVRKKpwBpxDJbEDgiA0N4LNNs3IyMBolN+BgiA0L7yKl7nr5nLP8nsoc5ZhM9t49KxHmTRwEiZjzbq10ler14od8Ljhy0fhm6fU7Wr9BhrC0oxjB/J9sQOZEjsgCIIgxBkivjZTAs1FtfsEynAyXw0GAykJZkrtbkodbrIC3K/YFzmQYDbW/zS/DlKDznzV8cb910/hw1vBfggS0mHkc9DzogZ3sZiMtEmxkl/mJK/EEYT4Kg23BEFoXgSTbWovL2XyBSeQmSnZpoIgNB92FO3gxo9v5MtdXwJwWqfTmHfRPI5pfUytsS6P1/8wvkbswKE98O5Y+GuNut1/rK/fgK3R8yc044ZbWuxAG3G+CoIgCHGGiK/NlBR/Lmr9S/NdHi8er1rQhStQauJreRBNt4pCiByAYMRXHWMH3E5YNhW+f0Hd7tAPLp0PrToHtHtWqs0nvtrp2T4tsFP6PhurOF8FQWhGSLapIAgtEa/iZc4Pc7hvxX1UuCpINCfy+JDHmXDyBIyGums9zfUK1WIHfvvc12+gCBLS4MJnavUbaAjN+epVwONVMAUYhxXvVDjd/q+XNNwSBEEQ4g0RX5spmkBZ1oBA6aj2xDsc5ytUE3sbEUSrE0qzLaguvjac+Wp3hZ9nC0DhTnh3DOzboG4PmgDnPAjmwAu7nHQbW/aXkFdiD3gfzZEgzldBEARBEISmy+8FvzP247F8vVttiHXGkWcw76J5dM3s2uB+lU5VTDQawIoHlj4I3z2rvtmuL1y2oM5+Aw1hrWZKcLq9Qa0+i2cKfJEDCWZjw83JBEEQBCEGiPjaTPFnvjbgRLVXe5oetvPV1vj5DieUZltQTXxtNPM1/DxbNn8IH98OjhKwZcDFL0L34UEfJjtNXf6UV+IIeB9puCUIgqAiWbGCIDRFPF4Ps7+fzQNfPEClu5JkSzIzzp3BLf1vqdftWp0Kn/ja1VqEYcFw2LtOfWPALXDuw/X2G2iI6nWl0+MlkeYhVBZokQMpCRgMYlwQBEEQ4gsRX5spKQE4XzXxNcFsDLtI0cTeoGIHfEVSq+Qgna8BNhNzhON8ddlh6QOw9hV1u+MAGD0PMjoGfyzU2AGA3CCcr1rsgIivgiC0dCQrVhCEpsa2/G2M+WgMq/esBuCcLufwykWv0Dmjc8DHqHR6GGpcy0zDS7C3HGzpMHIOHHthyPOyVFtR1ZxyXwvKVINDZrJEDgiCIAjxh4ivzZSqzNfGYwf0yEQN5HyHUxU7EFyRlGZTxdqAG24F63wt+APeuR5yf1a3T50EZ/8TTMGJxNXJTlPF1wMhxA5YJHZAEARBsmIFQWgSuL1uZq2exdQvp+LwOEi1pjJz6EzGnTguOLOD20nrb6byknWBut2hH1y6AFodGdb8DAYDVpMRp8frX2XVHNCcr5L3KgiCIMQjIr42U/yZrwHEDoSb9wqQHIL4qsUOZAYpvqZUa7ilKEq9hWxIDbd+eRcW3QHOMkhqDRfPhW7nBjW/ushJ98UOlAbjfPVlvsrSWUEQBEEQhLhn84HNjPloDGv3rQVgWNdhvHThS3RK7xTcgXz9BrJ9/QbeTRjFpWNeDqrfQENYzar42rycrz7xNTn4KAZBEARBiDQivjZTUhJUl2bDsQNqwaWH+BqLhltur4LdVX+jgCpnbwDX56qEJffB+oXqdqdT4NJ5kNY+qLnVhxY7EFTmq1uNHbDq4EwWBEEQBEEQIoPb62bGtzN4aOVDOD1O0hPSmTVsFmP6jgk+2qtavwGnNYNbym6kKOtsLtVJeIWqVVXNyflaWK7W2OJ8FQRBEOIREV+bKYE03HK4QnCG1kMgTtvDKQqx4Vay1YQBBQUDJXZX/eKrK8BYhYO/qTEDBzYDBjj9LjjjPjDp9+OhxQ7klzlwebwB5bi6/M5XiR0QBEEQBEGIR34+8DM3fXoTP+7/EYAR3UYw94K5dEjrENyBavUbGMiXx/6bLz7O49R6at1Q0R7sO5ql81XEV0EQBCH+EPG1mZIaQMMtreCKXeyA6nwNtuGWwWAg0QQVHii1u/zC5uH4Ywcaynzd+D/4dDK4KiC5LVzyMnQ9K6j5BELrZCtmowG3VyG/zEG79MRG93F5pOGWIAiCIAhCPOLyuHgr9y3enf8uLq+LVrZWPHPeM1zd5+rg3a4Ff8A710HuL+r2aXfCWQ9QuH4/kEeiDrV6dbTasjk5X/N9ma/ScEsQBEGIR0R8baZo4muly4Pb48Vch4BXlfmqY8OtoGIH1CIp2IZbADazKr6WBCAu1xk74CyHxXfDxtfV7S6nq8Jrak7QcwkEo9FAVmoC+w7ZySsJTHx1+wpii8QOCIIgCIIgxA0bczdy3QfX8fMBtTnryO4jeWHEC7RLbRf8wWr1G3gJug0BoNKp1uqJVn1v2TTna3PKfNViB9qkSOarIAiCEH+I+NpM0ZyooLpR6xI47W79Gm6FEjvgd76GIL4m+qZcUumqd0yV+HqYeHlgqxozcPBXMBjViIHT7wKjvq6Cw8lKs/nE18CabmluBIvEDgiCIAiCIMQcp8fJo6seZfo303F73aSaUplzwRyuPj4Et6urEj67F358Vd0+8lQY/UqNfgOVPqNEks7OV6vf+aroetxY4o8dkMxXQRAEIQ4R8bWZYjEZsVmM2F1eSu11i68BZ6IGQLLviXx5gOKr0+31C7Wtgmy4BZDo+84tbcj56s+09RWsigIb/qs6Xt2VkJKjFrldBgd9/lDITlOfxAcuvkrsgCAIgiAIQjywbt86xnw0hk0HNgFwSY9LuMh0EVf2ujJ44fXgb2rMwIEtqP0G7oYz7q3Vb6DCqda59fU3CBW/89Xj0fW4sUJRFAokdkAQBEGIY0R8bcakJFiwuxz1ulG12IEEHZ6mp9gab/BVneJKtUAyGiDNFrz4ajMpgKFB8dWuOV8tRnCUwSd3wi9vq292PVtd1pXSNuhzh0qOL5s2WOer2STOV0EQBEEQhFhgd9t5eOXDzPh2Bh7FQ9uktsw5fw6jjhnF4sWLgz9gjX4DWXDJS/X2G6jwxw5EJvPV6W4eztcyh9sfodA6WWIHBEEQhPhDxNdmTKrNTH5ZA+Kr1nCrrkzUINEyXwN1vmqRA+mJFowhLKvXnK8l9rpjB9weLx6vWlAmFW6FRTdCwXYwmODsB+DUO8EYXUdpll98dQQ03u1zvlrF+SoIgiAIghB1vt/zPWM+GsPW/K0AXHnclcw+bzZtk9victUffVUndfYbeAVSs+vdxR7h2AFnM2m4pUUOJFlNugvVgiAIgqAHIr42YxprglXlfI1+w60i39KgUPJeoSrztbQe8VXNe1X4u+kLUv7zX/A4ILU9XDofjhwU0jnDJTtI56vT73wV8VUQBEEQBCFaVLoqmfrlVGatmYVX8ZKdnM0LI17g4mMvDu2Ah/cbOPN+GDyl0X4DEXO++mIHXM2k4ZYWOSB5r4IgCEK8IqpOM0YTROuLAnDo6Xz1xQ6UOz14vY0vYSryOV8zQsh7BbD5xdd6rq38EM9anuUxyzwMHgd0Gwq3fBMz4RVCyXz1NdyS2AFBEARBEISo8O3ub+k7ty8zV8/Eq3i5us/VbL5tc2jCq6LAj6/BS2epwmtKDlz7MZxxT0CNXiMlvjY/56u6qkwiBwRBEOKb6dOnc9JJJ5GamkpWVhajRo1i27ZtNcbY7XbGjx9P69atSUlJYfTo0eTl5dUYs3v3bkaMGEFSUhJZWVncfffduN2BN3+PBSK+NmM0QbQx56tNR+crQLmz8W/64oowna9mVeCtU3zdt5G0V8/mQtMaXIoJzn0E/vYWJLcO6Vx6kRNi7IA03BIEQRAEQYgs5c5y7lxyJ4MXDOa3gt9on9qeRX9bxH8u/g+tk0KoIR2l8P5N8PHtaqPXrueoRoAgGr36Ywd0b7ilPth3NRPxtVBzvkqzLUEQhLhm5cqVjB8/njVr1rBs2TJcLhdDhw6lvLzcP+bOO+9k0aJFvPPOO6xcuZJ9+/ZxySWX+N/3eDyMGDECp9PJd999x6uvvsrChQuZOnVqLC4pYCR2oBmTqkUBOOpemm93+ZyvOuRIJZiNmI0G3F6FMoeb1EaaaFU5X8OLHSiprHZtigI/vAxLH8DscbJHacN9TOK/p94e0jn0Rst8PVTpwu7yNPp1r3K+ivgqCIIgCIIQKVbuWsnYj8fyR9EfAFzf93pmDZ1Fq8RWoR0w9xc1ZsDfb+CfcOqkoPsN+J2vFn1v2fzOV4kdEARBEKLIkiVLamwvXLiQrKws1q9fz+mnn86hQ4eYN28eb7zxBmeffTYACxYs4Nhjj2XNmjUMHDiQpUuXsmXLFpYvX052djZ9+/blkUce4d5772XatGlYrfH5t0BUnWZMY85Xh9uX+WoO/9vAYDA0er7qVDlfQ4wd8NWgfudrZTG8fQ18djd4nJR2HsYIx2P8aukR0vEjQZrN7HcZBxI94PJqma8SOyAIgiAIgqA3Zc4yJiyewJmvnskfRX9wRNoRLP77YhaMXBCa8KoosHYevHyOKrymdYDrP4XBk0Nq9BqxzNdmFzug3ldkSuyAIAhCTCgtLaWkpMT/z+EIbLXvoUOHAMjMzARg/fr1uFwuhgwZ4h/To0cPOnXqxOrVqwFYvXo1vXv3Jju7qmHlsGHDKCkpYfPmzXpdku6I+NqMSbU1kvmqo/MVINmqOW0bF1+LNPE1xOVBfuer3QV71sPcwbB1ERgtcN7j7DxnLodIIUGHPFu9MBgM1ZpuNf7LyOVWYwes4nwVBEEQBEHQlRU7VtD7hd7MWTsHgHEnjmPTrZsY3m14aAe0l8C7Y+DTyWqj127Dwu43ELnYgebmfFXr6jbifBUEQYgJPXv2JD093f9v+vTpje7j9XqZNGkSp556KscddxwAubm5WK1WMjIyaozNzs4mNzfXP6a68Kq9r70Xr8SFqjNnzhw6d+6MzWZjwIAB/PDDD/WOffnllxk8eDCtWrWiVatWDBkypMHxLZmUBNVVGo3MV6gSewMTX8NruJVoUgCF88veh/nDoHg3ZBwJYz+Hgbfi8OWl6uHq1ZMq8bVx56vbK7EDgiAIghAtpB5tGZQ4Srjlk1sY8p8h7CreRaf0Tiy9eikvXfgS6bb00A66bwPMPR02fwBGMwx9FP72JiRlhjXXCl8fhUSdjBIaWm3ZXDJfNeerxA4IgiDEhi1btnDo0CH/v/vvv7/RfcaPH8+mTZt48803ozDD2BNzVeett95i8uTJPPjgg/z4448cf/zxDBs2jAMHDtQ5/quvvuJvf/sbX375JatXr6Zjx44MHTqUvXv3Rnnm8Y8WA1BnUyrA7o8d0Keg05pulQcivpaH13Ar3VDGy5YnmeheAF4XHHsR3LwKOvQDqly91iYsvmpuBIkdEARBEITIIvVoy+Dz7Z9z3PPHMXf9XABu7X8rm27dxLldzw3tgIqCce3LMG8oFO2E9E4wZgmccntIMQOHE6nYgebnfJXYAUEQhFiSmppKWlqa/19CQsO/jydMmMAnn3zCl19+yRFHHOF/PScnB6fTSXFxcY3xeXl55OTk+Mfk5eXVel97L16JuTI1a9Ysxo0bx5gxY+jZsycvvvgiSUlJzJ8/v87xr7/+Orfddht9+/alR48evPLKK3i9XlasWBHlmcc/VQ23Gosd0OfbIDmhYbG3OlrsQCjOV8OeH7h01z851/QjDsWMd/hMuPw1SMzwj9FcvQk6OwXCJTtV/SUUmPNVYgcEQRAEIRpIPdq8KbYXM/ajsZz3+nn8VfIXXTK68MW1X/D8iOdJTUgN7aD2Q5y081lMS+8HjxN6XAC3rIKOJ+k270pnhGIH/M5XRdfjxoqCMjV2oHWIcWaCIAhCdFAUhQkTJvDBBx/wxRdf0KVLlxrv9+vXD4vFUqOe2rZtG7t372bQIDXGZ9CgQfzyyy81HpAvW7aMtLQ0evbsGZ0LCQF9W2cGidPpZP369TUsyUajkSFDhvjDdBujoqICl8vlD+g9HIfDUSPst7S0FACXy4XL5Qpj9vGP1pSqxO6s81orXapIajYounwtkq1qIXeowtHo8TTxNdVqDPzcihfjmucwfflvkhUPO73ZTHDdwX96XkWqu6bgW+FQj281GeLqc26boorN+4srG52XthRM8Xri6hr0QLue5nZdLQX5/Jo+sfoMXS4XiuLB6/U0OlZRPP6/1bJf7X3dblkVoRfRqEehZdeksWTx9sWM/2w8e0tVV/KE/hN45MxHSLYmh/x1N+z9EdMHY2l/6C8UowXvkIfw9h8HBgPo9Fm6PF7/g3iLTrW6htGgHrfS6W7y33uKolDoc76mJQRxX4HUM80B+Qzji1DrIACPR4nLuivcek27vmjuF841Bkuw+4wfP5433niDjz76iNTUVH9Ga3p6OomJiaSnpzN27FgmT55MZmYmaWlp3H777QwaNIiBAwcCMHToUHr27Mk111zDjBkzyM3N5Z///Cfjx49v1HEbS2Iqvubn5+PxeOoMy/31118DOsa9995L+/bta3RDq8706dN56KGHar2+atUqtmzZEvykmxDbDwGYySs4xOLFi2u9n19kAgxsXL+O8u3hP/kuPGAEjGz4ZQtti+rvMqcoUFyunvvH1V+zI4CfD6urhBN3v0R2yc8A7MkYyKi8sRxSkvnos2VkHnaMtQcNgInSooI6rz1W7MtX5/Xrn/tZvHhPveMUBVwe9cdz1VdfkBpaNG7cs2zZslhPQQgD+fyaPtH+DEtLS/ljrxFbcuNOM3t5Kcvsf5Camir71bHv6n35AY0VGica9Si07Jo0FpS6S5m/dz5fFn0JQDtrOyZ0mkAvdy9WLl8Z2kEVha4Hl9Bz79sY8VBuzWJdl9soPngEfPaZjrOHCjdot2orVyxDzyStnXvVenTnn7tZvHiXfgeOARVucHvVr9Par78I6esk9UzTRz7D+CDUOghg165d2JILgtqvKdRry+x/AER1v3CuMVjy84OrR1944QUAzjzzzBqvL1iwgOuvvx6Ap556CqPRyOjRo3E4HAwbNoznn3/eP9ZkMvHJJ59w6623MmjQIJKTk7nuuut4+OGHg55/NImp+Boujz/+OG+++SZfffUVNputzjH3338/kydP9m/v3buXnj17cvrpp9O5c+cozTQ2bN5XwrNb1oDZxvnnn1Hr/f/79WuorOT00wZxQseMsM+38bNtrDnwJ+2P7Mr5w46pd1xJpQvvGrUQHn3BsEajAQy7V2P64B4MZbkoZhvOcx5hfV4WppIkqHBx0qDBdM+p+YuidN0e2L6FI9plc/75J4R9bXrRZlchr/6+DrclmfPPP63ecS6PF9YsB+C8oeeSnti81FeXy8WyZcs499xzsVia17W1BOTza/rE6jMsLCxk59c7SErNaHRsRWkx5w4+iszMTNmvjn0HHdktoLFC5AmkHoWWXZNGm49/+5i7P7ub3PJcDBi44+Q7mHbGNJIsSaEftLII06IJGPd+DoC7+wV8lXABZ503MiK/R3NL7LB2FSajgQtHDMdg0M/tnvfdnyzavY2snPacf34f3Y4bC3YcLIe135JqM3PRBUOD2lfqmaaPfIbxRSh1UGpqKu+//z6dO3cmNaNVwPs1lXrt3MFHAUR1v3CuMVh27doV1HhFadz0Z7PZmDNnDnPmzKl3zJFHHhlXJrtAiKn42qZNG0wmU51huY0F5c6cOZPHH3+c5cuX06dP/UVDQkJCDetxSUkJABaLpdn/gm6Vot4AlDncdV6rwxeyn2JL0OVrkZao5ixVuLwNHq+sRF0alGgxkZJU/00KXi988yR8+RgoXmjdDcNlCzG27g6LF5OWaKGwwkWFm1rn0/oH2KzmuPqcO7RKASCvxIHZbK63kHYpVTEKSTYrFkuTfk5SLy3h57A5I59f0yfan6HFYsFgMGE0Np5faDCY/POT/WrvazY3z78LsSAa9Si07Jo0WuRX5DPxs4n8b9P/AOjeujsLRi5gUMdB4R149/fw7g1QsgdMCXDeYyjHX4v7s88i9vm5FbVeTrKYsFr1zTJNtKq/PzxK7Rq6qVHiVIv+1snWkK9FfgabPvIZxgeh1kEAJpMhLuuucOs17fqiuV841xgs8nMXODHt5GO1WunXr1+NMF2tWYEWplsXM2bM4JFHHmHJkiX0798/GlNtkqT4GmCVOz14vLWfMGhNqfRquOU/Xz0NvjSKKtRckMyGQvHLDsB/L4EvHlWF1z5Xwk1fQc5x/iGpNq3BV+2cEU1YTjDHWcOtNFVsrnR5KG3g61S9AYJZh265giAIgiDUjdSjzYP3trxHr+d78b9N/8NoMHLPKfew4eYN4QmvXi988zQsGK4Kr5ld4cblcNKNar5rBKlwqnVios7NtgAs/oZbXt2PHW38zbZS4jfnTxAEQRBibpuYPHky1113Hf379+fkk0/m6aefpry8nDFjxgBw7bXX0qFDB6ZPnw7AE088wdSpU3njjTfo3LmzP6A3JSWFlJSUmF1HPJJiq/p4y51u0mw1n0o4XD6BspFl/8Ger6xR8VV9kp+RVM9Tkh0r4f1xUJYH5kQY8SSccFWtYakJmvha+3x+8VUnYVkvEq0m0mxmSuxuDpTYa30mGtWLYYtJmqoIgiAIQiSRerTpcqD8ABMWT+CdLe8A0LNtTxaMXMDJHU4O78Dl+fDBLbDdlyV53KVw4dOQEHwmXihUOlWTRCTEV6svGFWrl5syBb5mWw2aOgRBEAQhxsRcfL3iiis4ePAgU6dOJTc3l759+7JkyRJ/04Pdu3djrOb8e+GFF3A6nVx66aU1jvPggw8ybdq0aE497kkwm7CajDg9XsrsNcVXr1fB6RP4bDol+GvO18bE12Kf+Noq6bAiyeuBlTNg5ROAAm2PhcsWQlaPOo/TsPNVLVgT9OxOoBPZaTZK7GXkHnJwdFbdBbzb53w1Gw26ZnwJgiAIglAbqUebHoqi8Pbmt5nw2QTyK/IxGUzcd9p9/Ov0f5FgDtMFuetbeG8slO4Hsw2Gz4ATr42427U6lb4Vaok6mSSq07ycr+p9RZsUEV8FQRCE+CXm4ivAhAkTmDBhQp3vffXVVzW2gw30bemk2MwUljtrCaLVn3Tb9HK+Bii+FpWrYmkN52tpLrx3I+z6Wt0+4WoY/n9grb8xQqpPTC6py/nqis/YAVDF198PlJFXYq93jFYMa8WxIAiCIAiRRerRpkNuWS63fXobH/z6AQB9svuwYOQCTmx3YngH9nrg61nwla/fQJtjVCNAdq/wJx0kFT7na1IEna/O5uB81WIHkiV2QBAEQYhf4kJ8FSJHqk98PXxpvpb3Cvq5Q/2xA3WIodWp5XzdvgLevwkq8sGSDBc8Bcdf0ej5NOdrSYOZr/EnXmq5r3mlgYiv4noVBEEQBEEA1e36+i+vM/GziRTZizAbzfxz8D+5f/D9WE1hOh/LDqixVzu+UreP/xucPxMSYhMjEdHYAb/ztfGu0/GOxA4IgiAITQERX5s5KQl1L83XxEmz0YBZJ3dlslVzvnoaHOdvuJVogBUPqw4DFMg+TnUXtOkW0Pkaznz1xQ7EWeYrQHaa+mT+QImj3jFaMSzOV0EQBEEQBNhXuo9bPrmFRb8tAuCEnBNYMHIBx+ccH/7Bq/cbsCSpomsd/QaiSVXsgP63a83L+aqKr60ldkAQBEGIY0R8bebUFwWgOV/1ihyAKidqmaO2E7U6RRVOcijgb1tnQvGP6ov9xsB508GSGPj5En3O18ra57PHeewAQO4hiR0QBEEQBEFoCEVRWLhxIXd+fieHHIewGC08eMaD3HPqPVhM9TRvDRSvR+01sHIGgfQbiCaRjB1oTpmvhT7nq8QOCIJ+eL1eiouLAx6fkZFRIxddEITaiPjazEmtJwrA7tbEV/1+SWpCr93lxe3x1uuoPbLgWx5OeJzM4jKwpsJFz8Bxo4M+XyDOVz2vTy8052sgsQNmiR0QBEEQBKGF8tehv7jpk5tYsn0JACe1P4kFIxfQK0uHDNaS/arb1d9v4Bq1sVYD/QaiSaVTrW8j0XBLc746moPztdyX+SrOV0HQjeLiYmZ9sgFbct3NoatjLy9l8gUnkJmZGYWZCULTRcTXZk79zlf9naHJCVXfTuUOD+lJhwmfHheseJi7C2aDAUpb9SL16v9A664hnU8Tlg+PVIDqma/x63xtKHbA7VVjB6zifBUEQRAEoYWhKAqv/PgKU5ZOodRZSoIpgYfPepjJgyZjNupw+3J4v4ELn4Y+l4d/XB2piGDmq9ZToKk7X71epcr5KuKrIOiKLTmV5LSMWE9DEJoNIr42c1JsdbtDHS79M1GtZiNWsxGn20upw0V6UrWlYMV/wbs3wJ4fAFjoHsoJI5/j+NbZIZ8vzaYev6Qu56sr/htuHSi14/UqGI213a0utzhfBUEQBEFoefxZ/CfjFo1j2Y5lAAw8YiALRi6gRxsdogA8bvjqsWr9Bnr7+g0cHf6xdUbLfI1E7IBWHzubuPhaXOnC51eoauQrCIIgCHGIiK/NnJQEVaCs5Xz1iXs2nZ2hqQlmCtzOmuf7dTF8eCvYiyEhnTsqx/KRuz8rU8PrHtuw89UnLseh+No2VY0dcHkUCiuctEmpnVHllMxXQRAEQRBaEF7Fy9x1c7ln+T2UOcuwmW38++x/c8eAOzAZdahXD+2F98bC7tXqdv8bYNh0sNjCP3YEqNScrxGIHfBnvjbx2IGCMnUVWUaSRWpmQRAEHQg279frbdp/R6KJiK/NnHozX12RyURNTjBTUO6k3OEGtxOWPwhrnlffbH8ijovn8dGTWwHICPMJdX2uXqgWOxCBgjVcLCYjbVKs5Jc5ySux1ym+uj3qY/z6cnMFQRAEQRCaCzuKdnDjxzfy5a4vATit02nMu2gex7Q+Rp8T/LYUPrgZKgt9/QZmw3GX6HPsCBHJ2AFrM3G+FvgiBzKTxfUqCIKgB8Hm/Y7uLVm/gSLiazOnvszXSGWiaudz5e+Ez++CfT+qbwwcD0OmUVzhBbZiMhpIs4X37aftX+H04PJ4azzxrrq++BQvs9Ns5Jc5OVDioFf72u9rGVxWiR0QBEEQBKGZ4lW8zPlhDvetuI8KVwWJ5kQeH/I4E06egNGgQw3n6zfAd7PV7XbHqzEDmUeFf+wIUxU7oP/tmt/56lFQFAWDoWnWmwVlqvjaJrm2kUEQBEEIDcn7jQwivjZzNDG0tFbDrcg4X1MSzJxn/IF+S+aBqxRsGTDqBehxPgBFFSUAZCRawi70Uqo1+Cqzu2lV7al3PMcOgCq+bt5XQl6Jvc73Xb4AK7MxPucvCIIgCIIQDr8X/M7Yj8fy9e6vATjjyDOYd9E8umaG1oi1FsW7ff0G1qrbJ98MQx8Bc9MQ6rTYgUhkvlqr1cdOjzcuG9QGQkG5GjsgzbYEQRCEeEfE12ZOij92oGYuqsMvvupYbLns3Fz+AudYPwIXcMTJcOl8yOjoH1JUrs4jo3ozrhCxmIwkWkxUujyUHi6+uiLj7NWL7DS18M+tT3z1OXctcSoeC4IgCIIghILH62H297N54IsHqHRXkmxJZsa5M7il/y36uF0Bfv0UPrzN32+Akc9Bz4v0OXaUqHCqxglda3Uf1mqrxVwehYQmekeoOV8ldkAQBEGId5ron1ohUPyZr7Wcrzovyy/4A965nnNKfwbgpyOv5/hrZ4KppshaXKEWSXp1JE1LNFPp8lByuLjsz3yNT/EyO01t7pBX4qjzfbdXYgcEQRAEQWhebMvfxpiPxrB6j9r06pwu5/DKRa/QOaOzPidwO2HZVPj+BXW7Qz/VCNBKp+NHkUpfrR4J52v1qC6n2wtNwwxciyrnaxO9AEEQBKHFEJ/KlKAbqQmq+Hl4UyptWb4uT9N/eRfmngG5P1NuSud659181XFCLeEVoKhCc77qI76m2tRz1BZf4z92AOBAPc5Xp0diBwRBEAT9mDZtGgaDoca/Hj16+N+32+2MHz+e1q1bk5KSwujRo8nLy6txjN27dzNixAiSkpLIysri7rvvxu2u3fRSEA7H7XUz49sZHP/i8azes5pUaypzL5jLsmuW6Se8Fu6E+UOrhNdBE2DMkiYpvAJU+pyvkRBfTUYDJqP6gN/VhJtuFfoabrUW56sgCIIQ54jztZlTFTtQt/M1LPHVVQlL7oP1C9XtTqcwP/M+vlpTRjeHq85divzO1/BjB6DK2VtdXFYUpZqzt2nGDrg9EjsgCIIg6EuvXr1Yvny5f9tsrioD77zzTj799FPeeecd0tPTmTBhApdccgnffvstAB6PhxEjRpCTk8N3333H/v37ufbaa7FYLDz22GNRvxah6bD5wGbGfDSGtfvU7NVhXYfx0oUv0Sm9k34n2fIRfDQBHCVqv4GLX4Tuw/U7fgyocEYgIqwaFpMBj1dRna9NlHxf7IBkvgqCIAjxjoivzRytKVWZ043Xq2D0PeXWGm6FvCw//3d453rI2wQYYPAUOPN+lK92Ar/VijnQKPI9oW6l0xPqNFttZ6+z2hN8vRuK6UVWasOxA5oLwWKU2AFBEARBH8xmMzk5ObVeP3ToEPPmzeONN97g7LPPBmDBggUce+yxrFmzhoEDB7J06VK2bNnC8uXLyc7Opm/fvjzyyCPce++9TJs2DatVxA+hJprb9aGVD+H0OElPSOepYU9xfd/rw2666sdlh6X/hLUvq9sdB8DoeTX6DTRVKl2Ra7gFau6r3eWtUTc3NQrKfLEDyRI7IAiCIMQ38alMCbqhOUMVBSp8RRxUy0QNxRn601tqzEDeJkhuC9e8D+f8C0xmkjWx1+Gpc9eq2AF9na8llVVOW0e1J/jx6nzNSVfF14JyR53LvVy+2IHqmVyCIAiCcDilpaWUlJT4/zkcdT/UA/j9999p3749Rx11FFdddRW7d+8GYP369bhcLoYMGeIf26NHDzp16sTq1Wo25+rVq+nduzfZ2dn+McOGDaOkpITNmzdH6OqEpsrPeT8z4JUBPPDFAzg9TkZ0G8Hm2zYz5oQx+gmvBX/AvHOrhNdTJ8H1nzYL4RWg0qmJr5Hxylh9q6uasvPVHzsgzldBEAQhzhFlp5mTYDZi9rknq0cPaM7XoJyhznL4cDx8cBO4yqHzYLjlG+h6tn9Iqia+2uuOHdC74VZqHc5Xhy9ywGBQl1TFI5lJVsxGA4oC+WW1b5Q1QdYcp/MXBEEQ4oOePXuSnp7u/zd9+vQ6xw0YMICFCxeyZMkSXnjhBXbu3MngwYMpLS0lNzcXq9VKRkZGjX2ys7PJzc0FIDc3t4bwqr2vvScIAE6Pk4e+eoj+L/Xnx/0/0srWitdGvcaivy2iQ1oH/U5Urd8ASa3hqvfg3Ifq7DfQFHG6vbi96oP4xAjFDlh9D/ibauar2+P1mzok81UQBEGIdyR2oJljMBhIsZkprnBR5nABquPS7nvKbQvUGXpgqxozcPBXwABn3gen3w3Gmvtrztfyep2v+oqvaf7M1+rO16pmW7q5K3TGaDSQlZrAvkN2cg/ZaZeeWON9f+yAOF8FQRCEBtiyZQsdOlSJWgkJdS+/HT68Kv+yT58+DBgwgCOPPJK3336bxMTEOvcRhGDYsH8DYz4aw095PwEwqsconj//edqlttPvJIf3GzjyVBj9CqS11+8ccYDmegVIjFDsgKWJO1814dVg0K+RryD8P3v3Hd5U/T1w/J3RJJ2UMloKhbK3DFGmLEEQQUBR3OAXUQREQBBxUEAZDhAHCAqC+kNxASogCkgBQTZFkQ1lyYaWzjTr/v5Ik7a00EFG057X8/R5SHLv/XySW9KTk3PPRwgh3EWSr6VAkN6efE3Oo/I1356vigJxi2HlGLCkQ1C4Pcit3j7vsRzJ0Bv0fE3MDJRcteBWiL/9OEnG3G0HimvLAYeKIQbOXjPm2ffV4mw7UDyTx0IIIYqH4OBgQkJCCr1faGgoderU4ejRo3Tt2hWTyURiYmKO6tcLFy44e8RGRESwffv2HMe4cOGC8zFRemVYMnhr41tM3zwdi81COf9yfNzjY/o37O/aL8EvHbYXAlz8F1BB+zHQ4RXQlLyPM45+r1q1ytkewNUcla++2vP1Sqo9fg4L0KGRNRKEEEIUcyUvWhG5OBfdypYQzShI5WtGCqwcDX9/a79doxM88BkEVSjAWHm3HXBWvrro8qBgZ+Vr7rYDejcFq64SEWKvQr6YbMz1mEkqX4UQQrhRSkoKx44d48knn+T222/Hz8+PdevW8eCDDwJw6NAhTp06RevWrQFo3bo1U6ZM4eLFi1SsWBGANWvWEBISQoMGDbz2PIR37Ty7k4HLB/LvJXvf334N+vHxvR8THhSez56FtHcJrBhtb3sVWMEej9bs5NoxipE0kz2udVfVK2TFmL5a+XolRfq9CpEfm81GYmJigbcPDQ1FrZbPn0K4gyRfSwFHgjLvnq83COrO77NXF1w5Aio1dHoN2o2GfN6Mg27SdsBmU7iW7p4Ft3IkXy0FrOr1svAQ+6WhF5JyJ18dla9aSb4KIYRwgTFjxtCrVy+qVavG2bNniYmJQaPR8Oijj1KmTBkGDRrE6NGjCQsLIyQkhBdeeIHWrVvTqlUrAO655x4aNGjAk08+yTvvvMP58+d5/fXXGTZs2A1bHYiSy2gxMil2Eu9ueRerYqVCQAXm3DeHfg36uXYgUyqsehni/s9+u3p7e+I1uGRXW6dlth1wV79XyFpwy7HIq6+5krnYVpj0exXihhITE5m5Yg+GwOB8tzWmJjO6ZzPCwsI8MDMhSh9JvpYCjoRo9lYAGTdacEtR7H20fh0H1gwIjoR+C6Bam4KNlUei1yHJaCZz7QBC/V3V89W32w4AnL924wW3dNJ2QAghhAucOXOGRx99lCtXrlChQgXatWvH1q1bqVDBfjXL+++/j1qt5sEHHyQjI4Nu3boxZ84c5/4ajYYVK1bw/PPP07p1awIDAxkwYACTJ0/21lMSXrL1zFb+99P/OHD5AACPNHqEj+79iPIB5V07UPb1BlRqe4uB9mNyrTdQEjmKJALcWPmq8/nKV3v8XC5IvvwR4mYMgcEEhoR6expClHqSfC0FgjMTlCnG3G0HciQojUmwYiTs+9F+u1ZX6DsPAssVeCxHotdktZFhseY4vqMxfpBe67L+VY7nlpzncyveVaPhN2k7YHb2fC3ez0EIIYRvWLJkyU0fNxgMzJ49m9mzZ99wm2rVqrFq1SpXT034iHRzOm+sf4P3t76PTbERHhjO3J5z6VOvj2sHUhTY83+wamzmegMRmesN3OXacYoxZ+Wrzn0f1bIqX30z+Xo1s/K1nFS+CiGE8AGSfC0FgvK4NN94feXrub326oKrx0GlgS4x0PqFfNsMXC8w2zf0qRnXJ1/tQZKrWg5A9rYD2SpfHYuJFfPkq6Pna15tBxyBsLQdEEIIIYS3bT61mf/9/D8OXzkMwJO3Pcms7rMI83fx5anXrzdQszP0/fSm6w2URFltB9wXBzoWdfXVBbcuO3q+BkrlqxBCiOJPkq+lQHAei2AZzY4Ft9Sw/TP47VWwmqBMFPT7HKLuLNJYWo0afz8N6WYrKUZLjj5MiY7FtgJc9w11iH9m24H0bIllx2JibuyT5QpZPV9ztx2w2KTtgBBCCCG8K9WUymt/vMaH2z5EQSEyOJJ5PefRs05P1w92fh98PwCuHLUXAnR+DdqOKnQhQEmQ1XbA/ZWvvtp24GqqPX4OkwW3hBBC+ABJvpYCQc7ka/YEpZUQUqn2x/NwPPMSwro9oPdsCLi1KoZAvdaefM3I2fc1IdW1i21BVuWryWrDaLZi8NP4TOWro+frtXSzc+4OJossuCWEEEII79lwYgODfh7EsYRjADzd9GlmdptJqCHUtQMpCuxaCL++km29gc+hWmvXjuNDstoOuK+QwNHaylfbDlzJrHwtL20HhBBC+ABJvpYCebUdqG0+zAzdLIKPXwK1H3SdDK2eB9WtV1oGG7RcTsnInXx1Q+VrkE6LSmWP25ONFnvy1UcW3AoxaJ1VwheSjFQrF+h8zFH5Kj1fhRBCCOFJKaYUXln7CrN32Pv/Vgmpwme9PqN7re6uH8yYBL+8CP8utd+u3Q36fFKo9QZKojSTPYb2d+NVXL5e+XrF0fNVFtwSQgjhAyT5WgrkqHxVFJStc1isnoBOZcVapiqahxdB5dvdMJ45x/2JmQtulXVh5atarSJIryXZaCHJaKZCsD4r+erGPlmuoFKpCA/Rc+JKGheSMnIkXx1VCH7SdkAIIYQQHrLu+Dqe+eUZTiSeAODZ5s/y7j3vEqIPcf1gZ+Pgh6ft6w2otXB3DLQeXirbDFwv3eRoO+DG5KvPV75mth2QylchhBA+QJKvpYDj0nzSEmDJY6gOrUKnglXWO2n39DeEhJZ36XiBenugmJJhzXF/1oJbrg2SQgx+JBstzsreDItvtB0Ae+uBE1fSOH/dolvmzLYDUvkqhBBCCHdLykji5TUvM2/XPACqlanG/Pvn06VGF9cPpij29QZ+fy3begMLIeoO14/lo9LN7m874MuVryaLjaTMuL+89HwVQgjhAyT5WgoE6f1orjrM25dnw6VLKBodE4yP8ZW1K4eCyrplPIAUY862A+6ofIWs5HKy0X78DLNvtB0ACM/s+3rx+uRrZtsBrVoqX4UQ7mOz2bh69WqBtw8NDUUtVWlClCi/Hf2Nwb8M5nTSaQCGthjK9C7TCdYHu36w9ET4eTgc+MV+u+590PvjW15voKRJ80Dlq+MLfpNVcdsY7uIo6NCoVYQYXPu5QgghhHAHSb6WdDYb1Q/P51vdO/gpVihbnYT7PuWr+ZdQqbIuOXIlRzL0+rYDzp6vLr48KPi6nrZZPV+Lf4IgIsTep+rC9clXR9sBH3gOQgjflZiYyEe/7cMQmH+SxZiazOiezQgLkySJECVBojGRl357ic/jPgegemh1Fty/gE7VO7lnwDO74IeBkHjKvt7APW9CyyEuWW+gpHG0HZCer3m7nK3lgFoKFUQpYLPZSExMLPD28mW5EMWPJF9LstQrsHwIlY/8DipYTRu6P/ctqWlaYD0GrQaVGwLeG7cdsCdj3dF2ACApPbPy1dF2oJj3fIWsytcLSRk57rdkViH4yR9NIYSbGQKDCQwJ9fY0hBAetPLwSp5b8Rz/Jf+HChUv3PkCU++eSqAuMP+dC0tRYOscWBMDNjOEVoOHFrp0vYGSJqvtgPs+qvn5cM/XKymZi21Jv1dRSiQmJjJzxR75slwIHybJ15Lq5Bb4YRAkn0XR6HnV+ATfKXdzVB+M8VoK4L7k5I3bDmRWvrqt7cD1la/Fv+1Axczk6/U9X02y4JYQQgghXOxq+lVG/TaKL/d+CUDtsNp83vtz2lVt554B067CT8Pg0Cr77fr3w/0fgX+oe8YrITzRdkDvw5WvV1Mzk6/S71WUIvJluRC+TZKvJY3NBn/OhPVTQbFCudoY+y7gm4/PAGA025zJSYObkpP5th1wceVrcGbla+6er8W/ajQ82N524Pqer47KV60suCWEEEIIF/jp4E8MWTmE8ynnUaFidOvRTO40mQC/APcMeHo7fP80JJ0BjQ66TYU7npE2AwWQbrYXFLiz7YDjC35frHx1tB0oF6j38kyEEEKIgpHka0mScgmWDobj6+23b+sP983EoAtErTqDTbEnKI2ZlzIZ3FT5Gpj5LX1qtrYDRrMVY2ZSNNTFla8h/vZf4yRn5Wtm2wEfSL5GlMlqO6AoirMNhCMQdkdPXiGEEEKUHpfTLjPi1xF8s+8bAOqVr8fn939O66jW7hnQZoMtH8K6yfZCgLAa8NAiqNTEPeOVQM6er26sfHXEmBk+mHx1VL6GSdsBIYQQPkKSryVF/Eb48RlIuQBaf7jvPWj6OKhUqIAgvZYko4XkDIszCWpw07fpQY5K1IystgOOqletWkWQ3rW/do7K16TMyld3Pz9XqhhsT76mm60kZ1ic/WvNjp6vWqkOEUIUP7LwgxC+4cf9PzJ01VAupl5ErVIzts1YJnaciEFrcM+AqVdg2XNwdI39dqMHoecsMIS4Z7wSyhNtBxyLupp9sO2Ao+dreWk7IIQQwkdI8tXX2ayw8V3Y8DYoNqhQz15dULF+js2CDX4kGS2kGC1urwwN0jsqX7MlX1OzFtty9SJfuXu++s6CW/46DSEGe2L8wjVjtuSrPRDWSrJCCFEMycIPQhRvF1MvMnzVcL7f/z0ADSs0ZGHvhdxR+Q73DZptvQG0Brj3bWg+QNoMFIFzwS23th3I7Pnqg5WvV1Iz2w4ESdsBIYQQvkGSr74s+by92vXEJvvtZk/Ave+CLnfvLke1aUq2yle9uypf81hwK8FNi20BzoRlUnpmz1cfWnALIDzEQJIxhQtJGdQOtycyLNJ2QAhRzMnCD0IUP4qi8N2/3zH81+FcTruMRqVhfLvxvN7+dfRaNyWqbDb4c0bmegM2KFfbXggQ0cg945UCnmg74CjC8MWer1ek7YAQQggfI8lXX3XsD1j6LKReAr9A6DkTmjxyw82DslWHZvV8dVfbgaxEr4Mz+eqGICl35avvLLgF9r6vRy6mcCHboltm54JbUi0ihBBCiPydTznP0JVDWXZwGQC3hd/Gwt4LaV6pufsGTbloj0ed6w08AvfNAH2Q+8YsBdKdbQfc91HNWfkqbQeEEEIIt5Pkq6+xWiB2GmyaAShQsaG9uqBCnZvulr3y1VNtB3ImX+1Vqe6ofA129pjNrHw1O56fb1S+Ovq+ns9MviqK4rwEzE8qX4UQQghxE4qisPifxYz4dQQJxgS0ai2v3/U64+8aj07jxuTU8Q32hV6d6w3MgGaPu2+8UkJRFNLM7u/5qnO2HVDcNoa7ZC24JW0HhBBC+AZJvvqSa//Z2wyc2mK/ffvT0H0a+Pnnu6uzGtVoxpYZY7mt8tXRdiDDgqIoqFQqElMdbQdc/yGgjL/9uSWl25O9jm/wfaHnK0B4iD1wvJiZfLXasoJgP6l8FUIIIcQNnE0+y3MrnmPF4RUANItoxsLeC2kS0cR9g9qssOEd+3oDKFChfuZ6A/XcN2YpYrLanLGgOxePdSy45WuVr0az1VngUU4qX4UQQvgISb76iiNr7Jd1pV8FXTD0mgWN+xV49+Bsla9qtT2hZ3BX5WtmotdqUzCabfjrNM7K11A3JF8dla+OZK+vtR0ID7FXvl5Isi8eYLZmT776xnMQQgghhOcoisIXe79g1G+jSDQm4qf2I6ZDDC+3fRk/jeuvMnIqxHoDomiMpqxkqCcqX32t56uj36tOo3Z+vhFCCCGKO/mLVdxZzfDHm7D5A/vtiNvs1QXlahbqMI62A8kZFufl+O76Nj0g23FTMiz46zQkunHBreBsyd40kzVbWwXfaDvgTL4m2ytfzbasIFh6vgohhBAiu9PXTvPciuf49eivALSIbMHC3gtpVNHNC1zlWm/gfWjS371jlkJpZntVp59G5dYv4XVae4zpa5WvV1OyFttSqSROFkII4Rsk+VqcJZ6GH/4HZ7bbb98xGO55C/wMhT5UVtsBC2Tu7q7KULVaRZBeS0qGhZQMCxWC9VkLbrmh8tXfT4NWrcJiU0gymskw+1rlq73twIVrmcnXbEGwn9o3noMQQggh3EtRFObvns+YNWNIykhCr9EzqeMkXmrzElq1G0P669cbCG9kLwQoX9t9Y5ZiaSb3LozroNPYj+9rla+XU+1XiknLASGEEL5Ekq/F1cFVsPx5MCaCvgz0/gga9C7y4bJfmu/4Ft2dQV2gXkNKhoXUzJ5MWW0HXF/5qlKpCDZoSUgzk2y0ZLUd8Jmer/Zs+MXkDGw2BUtmny+NWuVsEeFqVqsVs9nslmMXhNlsRqvVYjQasVqtXpuHKJricv40Gg1arVYqX4QQJd7JxJMM/mUwa46vAaBVlVYs7L2QeuXd3Gf1FtYbEEWTbnL/YlsAfsWg8lVRFCwWS6FiieSUNCoHa6gZpsNoNN7S+MUlnhFFVxzOocSjQoiCkORrcWMxwdqJsHW2/XZkc+j3OYRVv6XDOnoiJRst+Ps52g64LzkZpNdygQySjfbkq7PtQKB7vqUONviRkGbmWroZk9VR+eobbQcqBOtRqcBiU7iaZnIGwe5abCslJYUzZ86gKN5b3VZRFCIiIjh9+rQEKj6oOJ2/gIAAKlWqhE4nFTBCiJLHptiYt3MeL699mRRTCgatgSmdp/BiyxfRqN0c5xz+HZY9l7XewP0fQKMH3TumIN3sSL6692Oao+eryUuVryaTiXPnzpGWllao/SLUZiZ2qkiATkN8fPwtzaE4xTOiaIrLOZR4VAiRH0m+FicJJ+xtBv7bZb/daih0mQTaW38Tz952ICTz3+5MTgZlq7SFrMpXd/R8hay+r5eTM5z3uTO57Ep+GjXlAvVcTsngQpLRGWy7o8+X1WrlzJkzBAQEUKFCBa8FKTabjZSUFIKCglBLawWfUxzOn6IomEwmLl26RHx8PLVr15bfJSFEiXI84TjP/PwM60+sB6Bd1XYsuH8BdcrVce/AVjOsmwxbPrTfrtQE+i0s9HoDomg81XbAEWd6o/LVZrMRHx+PRqMhMjISna7g/VsvJhvRp5ooG6CjYkjhW7FdPw9vxzPi1nj7HEo8KoQoKEm+Fhf7f4afhkPGNTCEQp9PoF4Plx0++4Jbjsvy3Vv5ag8YUzMsWDN7sQKEuqHnK0BIZrL3UkpW8lXnxkUKXC08JCv5WqWsfcVgdyRfzWYziqJQoUIF/P29d8mgzWbDZDJhMBgkQPFBxeX8+fv74+fnx8mTJ53zEUIIX2dTbMzePptX1r1CmjmNAL8Apt09jeF3DketcvN77vXrDdz5HNzzJmj17h1XOHmq7YBjbQRv9Hw1mUzYbDaioqIICAgo1L6qNBsqLRj8Dbf8d7+4xDOi6IrDOSxMPGqz2UhMTCzwsUNDQ+V3U4gSQpKv3mbJgN9fh+2f2m9XucPeZiC0qkuHcVa+ZpgxZl7OpHfjN+rZk73X0s04rnAP9fdM5atWrULrU8lXA/+eTeJCUoazB6y72g4AcmmVKDEkIBVClDRv/PEGU/+cCkDH6I7M7zWfmmEeqDrNtd7Ax9DgfvePK3JIN9uvGnN7z9fMONmmgMVq80rcXJS/4Y61EbTy918UIwX9XU5MTGTmij0YAoPz3daYmszons0ICwu71ekJIYoBSb5605Vj8MPTcG6v/XbbF6HzG6BxfYLS0fM1xWjBaHZUvroz+ernHC8hs99rsEHrtsAu2Fn5ah/L8W2+r3AkXC8kGTFbQwAJKoUQQojSaOgdQ/ny7y8Z3248Q1oMcX+1q8UEa2Ng6xz77cjm8NBCKBvt3nFFnjzVdkCXLVY2WxV8ZKkErDb75xitmxalFcLdDIHBBIaEensaQggPk+Srt+z7EX5+EUzJ4B8GfedBnXvcNlxW5asFoyWz8tWNCcrsbQeci225qeUAQIi//fldyqx8dWdVrzuEh9gv57uQlOG8/EvnoQRyYS9/cYWQkBCPjieEEEL4isohlTn6wlH0nrjUP+EEfP80nN1tv91qGHSZ6JL1BkTReKrtQPb2ViaLDX83j5efgsajly8nYbYqJGlMWNJv7aOsxKNCCCE8RZKvnmZOh9XjYddC++2qreHBBVCmsluHdbQBMFsVktLt/VfdWvmaLdmbkOrexbYgq/L1cmbPV9+ufPXsN/qFufzFFYypyYzs0QSt1nfefk6cOEH16tXZs2cPTZs29fZ0ADh48CADBw4kLi6OevXqERcX57GxJ02axNKlS9m7d6/HxhRCiNLEI4lXN683IIrGc8nXrDjT5IW+r9craDx6OSUDRYFyQX63VBUu8ahreDMenThxIsuXLyc2NtZjYwohRFH5zl+bkuDyEfh+IFzYB6jgrtHQ8VXQuP80BOqyxriceWm+wY0JykB9tuRrZuWruxbbAghx9Hz12eSro/LViNlq72XljgW3bqS4X/4ycOBAvvjiC6ZNm8Yrr7zivH/58uX07dsXxdFUuBSJiYkhMDCQQ4cOERQU5NGxX3rpJQYMGODRMYUQQriI2Qhr3si23sCdmesNRHl3XgKAtMy1Gfz93Pv5QKVSodOoMVltXll0Ky/5xaOKomDAHusHBes9voaBxKO5eTMeHTNmDMOGDfPomEIIUVS+laHyZXu/hXkd7InXgPLwxI9w9wSPJF4B1GqVs/r1Wmblqzsvzc/eYzYxzf2VryGOnq+OtgO+0rgqU1blawaWzADYnQtu+SKDwcDbb79NQkKCt6fiMiaTqcj7Hjt2jHbt2lGtWjXKlSvn9vGyCwoKkub/Qgjhi64cgwVdsxKvbV+Ep1dJ4rUYcVS++uvc/zHN0eLKZCkeydf82DKTmyqV/ccbJB7NydvxaEHHFEIIb5Pkq7uZ0uCnYbDsWTCnQvRd8PxmqHW3x6fiSL46GPzc2PPV4NnK1+DM8TIyg0e9G5+bOziSr1dSM5wLLXiy8tUXdOnShYiICKZNm3bDbSZOnJjrMqxZs2YRHR3tvD1w4ED69OnD1KlTCQ8PJzQ0lMmTJ2OxWBg7dixhYWFUqVKFhQsX5jr+wYMHadOmDQaDgUaNGrFhw4Ycj+/bt497772XoKAgwsPDefLJJ7l8+bLz8Y4dOzJ8+HBGjhxJ+fLl6datW57Pw2azMXnyZKpUqYJer6dp06asXr3a+bhKpWLXrl1MnjwZlUrFxIkT8zzOjca72Tw//fRTIiMjsdlyfhDr3bs3//vf/wB724G77rorx+Pz58+nfv36GAwG6tWrx5w5c5yP9evXj+HDhztvjxw5EpVKxcGDBwF7EB4YGMjatWsB+OGHH2jcuDH+/v6UK1eOLl26kJqamudzFEIIUUD7frQXApz/277ewGPfQ9fJblnoVRRdVtsB9xdoOL7oLy6Vr/mxZRaWqlUqwDvZV4lHi088OnHiRJo3b57jcYlHhRDFlWR33OniQfisM+z5P0AFHV6Bp36C4AivTMeRoHQwuLE61NHmwJ58dVS+ujP5mvODg6+1HQgL0KFVq1AUOHctHQCtVL7moNFomDp1Kh999BFnzpy5pWP98ccfnD17lo0bNzJz5kxiYmLo2bMnZcuWZdu2bQwZMoTnnnsu1zhjx47lpZdeYs+ePbRu3ZpevXpx5coVwN6rrHPnzjRr1oydO3eyevVqLly4wMMPP5zjGF988QU6nY7Nmzczd+7cPOf3wQcfMGPGDN577z3+/vtvunXrxv3338+RI0cAOHfuHA0bNuSll17i3LlzjBkz5obP9frx8pvnQw89xJUrV1i/fr3zGFevXmX16tU8/vjjeY6xePFiJkyYwJQpUzhw4ABTp07ljTfe4IsvvgCgQ4cOOfpxbdiwgfLlyzvv27FjB2azmTZt2nDu3DkeffRR/ve//3HgwAFiY2N54IEHSsWlfDabjatXrxbqx/GhpLD7Xv9hRghRgpnT4ZeR8MP/7Au9Vm0DQ/5060Kvouiy2g64/youR+Vrho9VvnpoWYQ8STwq8agQQhSF9Hx1B0WBuMWwcgxY0iEoHB74DGp08Oq0gq5Pvnpowa3EzMrXsoFubDvg77nn5g5qtYqKwXrOXjNyJsGefJXK19z69u1L06ZNiYmJYcGCBUU+TlhYGB9++CFqtZq6devyzjvvkJaWxquvvgrA+PHjmT59On/++SePPPKIc7/hw4fz4IMPAvDJJ5+wevVqFixYwMsvv8zHH39Ms2bNmDp1qnP7zz//nKioKA4fPkydOnUAqF27Nu+8885N5/fee+8xbtw459hvv/0269evZ9asWcyePZuIiAi0Wi1BQUFERNz8y5zrx3vrrbfynee9997L119/zd132yv0f/jhB8qXL0+nTp3yHCMmJoYZM2bwwAMPAFC9enX279/PvHnzGDBgAB07duTFF1/k0qVLaLVa9u/fzxtvvEFsbCxDhgwhNjaWO+64g4CAAA4ePIjFYuGBBx6gWrVqADRu3Pimz7GkKOzid8bUZEb3bEZYWFih9jWmJvNCt0a3Ol0hhC+4fr2B9mPsxQAeanslCi/dZAHA380LbkFWrOmbla/eI/GoxKNCCFFYEnm5WkYKrHwJ/l5iv12jEzzwKQRV9O68yN12wJ3VocF6e6I1xeiptgO+XfkKEF7GwNlrRv7LTL7qJPmap7fffpvOnTvf9Nv1/DRs2BC1Ouv1DQ8Pp1GjrGSURqOhXLlyXLx4Mcd+rVu3dv5bq9XSokULDhw4AMDevXtZv359nosNHDt2zBns3n777TedW1JSEmfPnqVt27Y57m/bti179+4t4DPMcv14BZnn448/zuDBg5kzZw56vZ7FixfzyCOP5HjNHFJTUzl27BiDBg1i8ODBzvstFgtlypQBoFGjRoSFhbFhwwZ0Oh3NmjWjZ8+ezJ49G7BXHnTs2BGAJk2acPfdd9O4cWO6devGPffcQ79+/Shbtmyhn7svupXF74r7wnlCCA/b+y2sGGVvexVYwR6P1uzs7VmJfKSbHW0HPFf56ms9X72dfAWJRwuruMaj3bt3Z/bs2VgsFmJjY2nfvj0Wi4WGDRvSuXNnGjduzD333EOXLl148MEHKV++PABWqzXH+BaLBZvNRmJiIjpd7s+8oaGhec5bCFF6SPLVlc7vgx+ehsuHQaWGTq9Cu5egmLzR5mo74Mbq0EC9/dipGZ5ZcOv65+ZrC24BhAfb+746Kl+l7UDe2rdvT7du3Rg/fjwDBw7M8Zharc51OZDZbM51DD+/nL+LKpUqz/sKc2l2SkoKvXr14u233871WKVKlZz/DgwMLPAxXeH68Qoyz169eqEoCitXruSOO+5g06ZNvP/++3kePyUlBYDPPvuMli1b5nhMo7H/P1SpVLRv357Y2Fj0ej0dO3bktttuIyMjg3379rFlyxbnhxeNRsOaNWvYsmULv//+Ox999BGvvfYa27Zto3r16rf2YgghRGlgSoNfx2a2vcK+3sCD873W9koUjqP3v0faDjgrX33jUmpbZulrcfhoJfFo4RTHeLR9+/aEV62F0ZjBxm272fLXX/xvyAtczFzA+cvvf2Lntq1sWL+ODz/6mNffeIO/tmyhevXqXEhMQ6XJ+j9qMZlINpr5ffspUq871dmvVBJClF6SfHUFRYFdi2D1K2AxQnAleHABRLfNd1dP8mTlq7PtgMnC1dTMtgMeWHDLwScrX0P0AJxJSAOk7cDNTJ8+naZNm1K3bt0c91eoUIHz58+jKAqqzKqIuLg4l427detW2rdvD9i/4d61a5ezcX/z5s358ccfiY6ORqst+ltrSEgIkZGRbN68mQ4dslqVbN68mTvvvPPWnkAB52kwGHjggQdYvHgxR48epW7durkWNHAIDw8nMjKS48eP37AHF9j7bH322Wfo9XqmTJmCWq2mffv2vPvuu2RkZOSorFCpVLRt25a2bdsyYcIEqlWrxrJlyxg9evStPXkhhCjpLh6wtxm4dBBQQcdXoP1YUPvel9KllWPBLU+0HXBWvl5XxVdcKcWk7YCDxKNFVxzi0cmTJ6Px86NV27bMnf0hpowMWrZp60zWArRq245WbdsxZvzr3N6wDsuXL2fUqFGoNJoc29k0GlQqNf6BwWCT91shRG6SfL1VxiRYMdK+gixAra7Qdy4ElvfqtPISpM/6JlWnUaN2Y7d6R6JXUeBSiv3bw7KB7ku+6rUa9Fq1c8EAvZ/vJS7Dy9grX1Mzg25PJl+Nqck+NVbjxo15/PHH+fDDD3Pc37FjRy5dusQ777xDv379WL16Nb/++ishISG3PCbA7NmzqV27NvXr1+f9998nISHBueLqsGHD+Oyzz3j00Ud5+eWXCQsL4+jRoyxZsoT58+fnCNDyM3bsWGJiYqhZsyZNmzZl4cKFxMXFsXjx4lt+DgWd5+OPP07Pnj35999/eeKJJ256zEmTJjFixAjKlClD9+7dycjIYOfOnSQkJDgTph07dmTUqFHodDratWvnvG/MmDHccccdzoqIbdu2sW7dOu655x4qVqzItm3buHTpEvXr17/l5y6EECVWXusNPDgfqrf39sxEIXmy7YAj1jRZikfla34xYmq6mQyLDa1Fi3KLV7lJPJq/kh6Ptm3bljQF2rRrz6TXx9O0+e3OeHT3zu1sio2lQ+e7KV+hArt37uDqlcsSjwohikySr7fi3F57dcHV46DSwN0ToM2I4nEtTB6yL7jl7uSkv58GtcreGN/xLbU72w6Ave9rRmai15fbDjj4eajtQGhoKKN7NvPIWA4hISHOy4OKavLkyXz77bc57qtfvz5z5sxh6tSpvPnmmzz44IOMGTOGTz/99JbGcpg+fTrTp08nLi6OWrVq8fPPPzt7PzmqA8aNG8c999xDRkYG1apVo3v37oXu8TRixAiuXbvGSy+9xMWLF2nQoAE///wztWvXvuXnUNB5du7cmbCwMA4dOsRjjz1202M+88wzBAQE8O677zJ27FgCAwNp3LgxI0eOdG7TuHFjQkNDqVOnjrO/V8eOHbFarc5+r2D/3di4cSOzZs0iKSmJatWqMWPGDO69995bfu5CCFEi5bnewGcQVMG78xJFktV2wP0f0xyxpqkYLLhVkHj02MVkjGYbUeUCCDHc+ucKiUdvrjTEo2nJGbRp1x6r1UqbdllfVgUFh7B1y598+snHpCQnUSWqKhPenEr37t1v+bkLIUonSb4WhaLAjvnw26tgNUFIFej3OVRtmf++XhScre2AO/u9gv2y4SC9liSjfcVWnVbt9t5VIQYtl53J1+KZAL+Z8JCcyVethypf1Wq1x3sQFaZ3FcCiRYty3RcdHU1GRkau+4cMGcKQIUNy3OdYNfZGx4qNjc1134kTJ3KM5ejd9eijj95wnrVr12bp0qU3fDyvcfKiVquJiYkhJibmhtsU5PK1G42X3zwdczh79myej8XExDBq1Kgc9z322GM3DYrVajVXr17NcV/Tpk1z9USrX78+q1evvunchBBCZDq/z14IcOVI5noDr0G70cW2EEDkz9F2wDMLbtnHMBeDBbcKEo9eyNCit9qoWD6IAN2tf4yVePTmins8OnHiRCZMmEBSUpLzvsLEoxaL/XNqo9uacP5aeo7t6tStxzdLf85x3/WLbAkhRGFI8rWwjNfg5xdg/0/223XuhT5zIKD4N9DOXvlq8MBl+dmTr2UD/Jw9j9wl2D/rG3DfTL7qc9zWSc9XIbzKsWptYchqtkIIj8i13kAk9FsA1dp4e2biFiiKQprJHjt7pOdrMap8zY+iKFgyF9zSyt9ZkY2iKFit1kIl0wvTfkEIIVxBkq+F8d8u+P5pSDwJaj/oOglaDYVi0vQ9P9kX3PLEZflBBi1cs//bnYttOYTkaKvge39QHT1fHbRu7MkrhMhfYmIiM1fswRAYXKDtHavZhoaGFilpK4QQBZLnegPzILCcV6clbp3JaiMzv+jRBbfMPpB8tSmKs+pTYmSRnc1m48K1NNSagqU2FKuV8NAAN89KCCFykuRrQSgKbJsLv78BNjOEVoV+i6DK7d6eWaF4o/LVIdTN/V4BgrMnX32w8jVYr8XfT+NcaMHPB5+DECWNITCYwJDQQu1T1KStEELk6/r1BrrEQOsXpM1ACeFoOQC4vV0XZF9wq/gnXy1We+JVrVK5ddFg4ZvUak2Bq1mleYAQwhsk+ZqftKvw03A4tNJ+u34vuP9j8A/16rSKIntlqMEDla+B2ZKvnql89e22AyqVivAQPSeupAHgJ4GlED6rKElbIYS4oevXGygTZV9vIOpOb89MuJBjsS0/jcqZGHUnR4srX2g74Gw54KEFaYUQQghXkuTrzZzeAT88DddOg0YH90yBOwf7TJuB6wXpsyUnPVD5mr0SNdQDyddgH287AFAxxJCVfHVj0H39IkdC+Cr5XRZClHjpifDLiKz1Bur2gN6zfWK9AVE4jqufPFH1CllXWXmr8rUwf8Ol32vJ5+jdWlDFqm+r83fZN/MEQgj3k+RrXmw2+OsjWDcZbBYoWx0eWgSRTb09s1sS5OHK16Acla+eaDvg25WvABEhWX1f3dF2wBGkmEwm/P39XX58ITwtLS3zywo/97/HCCGEx+Vab2AytHreZwsBxM052g4E6DzzEc1R+erpnq+Ov9lpaWkFjkctmYspSb/X4q8oSVSVSoXVauVCYhqqAiRVHX1bi8sip6YMI1ZFwWST308hRN4k+Xq91Cuw/Hk48pv9dsMHoNcHYAjx7rxcIHsy1OCBb9Q933bAswuKuUN4iN75b3cEl1qtloCAAC5duoSfn5/XAhabzYbJZMJoNBaboEkUXHE4f4qikJaWxsWLFwkNDS1e1Q9CCHGrFAW2fgJrJmSuN1ANHloIlX1rvQFROI62A55YbAuyFtzydOWrRqMhNDSUixcvAhAQEIAqny8UjOkZKBYTWBSMRte8PsUhnimJLBYLV5KNqArwmio2G+WCDWi1WiwWC1arBTX5V0TbrFbneTOZTFhUYLMVLOFr39c+hsVkwlbAGDLP/RQFU4aRK5cvcTZNjVUqX4UQNyDJ1+xO/gU//A+Sz4JGD/dOh9ufLjHVBdmTrx5pO+DxBbc821bBHcKzVb7q3FD5qlKpqFSpEvHx8Zw8edLlxy8oRVFIT0/H398/32BbFD/F6fyFhoYSERHh1TkIIYRLpV2Fn4bBoVX22/Xvh/s/8sn1BkTheLrtQFblq+db+Dj+djsSsPlJTDOTkmEh3aAlPcE1nyuKUzxTHCmKUqjWECqVCpVKhc1mI9loRqUqQPJVsZFisBeEFHa/ZIMfKpWK1NRULGo/1AXYL/u+QIHHu9l+VkXhbJqa00b3FxsJIXyXJF/B3mZg8/vwxxRQrFCulr3NQERjb8/MpTRqFQE6DWkmq0cqQz1d+Zqj56uPth2omC356q6eVjqdjtq1a2Mymdxy/IIwm81s3LiR9u3by+XiPqi4nD8/Pz+peBVClCynt9sLARzrDXSbCnc8U2IKAcTNpZssAAR4qPLVsb5Ahhd6vjoKAipWrIjZbM53+ykr9/PHwYsM6VCThxpEuWQOxSWeKa4SExNZFHsAfUBgvttmpKUysGN9QkNDSUxM5Pftp/APDM53v/TUZB69M6LI+wUGBvLrr79yRh9FQFBoQZ6Wc1+gwOPdeD8VJptKKl6FEPmS5GvKJVj2LBz7w377tv5w30zQB3l3Xm4SpNeSZrJi8EBlaPYes2UD3R/QhPhn7/nqmwmZHD1f3biaq1qtxmAw5L+hm2g0GiwWCwaDQYJdH+Rr589ms5GYmFjg7UNDQ+XyQyGEZ5XQ9QZE4Xir7YCne75mp9FoCvRFanyCmf+SrQQF+rsshvW1eMbTdDodFr9A9AWoureY7dsbDAZ0Oh2pZsCW/3lNdcF+JpOJVDWoCrBf9n0d/y7IeLeynxBCABSLT5ezZ88mOjoag8FAy5Yt2b59+023//7776lXrx4Gg4HGjRuzatWqog0cvwnmtrMnXrX+cP/H0HdeiU28QlZC1BM9X4NytB2QyteCyN7z1VGNIISws9lsXL16tcA/tszFORITE5m5Yg9z1h/N92fmij2FStQK4WsKG3OVJl6LR9MS4Jv+mf1dLfb1Bp7bKInXUsiZfPVQ2wHHF/2e7vlaFJdTMgAoF6jPZ0shhBDFXWmMR71e+frtt98yevRo5s6dS8uWLZk1axbdunXj0KFDVKxYMdf2W7Zs4dFHH2XatGn07NmTr7/+mj59+rB7924aNWpU4HFV2z6Bg5+CYoPydeHhL6BifVc+tWLJ0YfVE8nJII8vuJX1jbUnKnvdoWJw9spX33wOQriLI4lqKMDlYcbUZEb3bEZYWBgAhsBgAkNC3TxDIYq3wsZcpYm34lEAzTf9QHM5c72Bt+H2gdJmoJQyZvZ89VTbAX0xqHwtqKup9nZZYYGu/0zh+HK3oBxXyBT1yhpf2U8IIdyhtMajXk++zpw5k8GDB/P0008DMHfuXFauXMnnn3/OK6+8kmv7Dz74gO7duzN27FgA3nzzTdasWcPHH3/M3LlzCzyuautsrurU0Ogh6DoRtIFwkz+63vrj5erx8qt8deV4juSrSgVl/PO+lKew4wEEBubddyhn5euNg9biHLj46zSEGLQkGS2oVUqJDQQhK9At6GVeRR0v+5ie3M9XzkVR9nP8H/T0hxWQJKoQt6KwMVdp4q14FECVehGq181cb6AR/yWm88+ZxFt9SsLNLBYre6+o0Px7Aa2L2l39feYaAP66G39Ec2U86vii/7/EdFbvO3fD8VKTrxV4vMDgMs6/9YXZL/u+eXEkX8sH5V35eiufKRITE/not32F/nK3qF8K+8p+QgjhDqU1HvVq8tVkMrFr1y7Gjx/vvE+tVtOlSxf++uuvPPf566+/GD16dI77unXrxvLly/PcPiMjg4yMDOfta9fsQcDhRC3fVXwR3ZX6sGTzzedpTOP5bs0oW7YsCQkJfPLbHnSGgPyfX7b9ABISEvLdxyH7Pq4cz3zpBBmXrnLppIo9e5LcOt5/l1PJuHSSEL2Gv/fG5fkcCzOeY8zBdzfm8uXLxMXFodVm/QpbbQrmyyexKXD0wD9cvq7a9lafo6fOfagtmatJqfx37CCvrDzhsXl6cr+goCBOnz7Na/N/wRCYf5uPoo6XfV/Ao/v5yrkoyn6O/4N///03n637x6PzvHDmBIaA/H9njGkpnDzpR1JSkkf2y74v4NH9ivIcT51ScfnyZU6dOlVsX1PZ7+b7/qe3//+5du0aISEhzsf0ej16fe7kRFFirtLCE/Eo3Dgm/TegNZdaxsA5M5zbwx+HLvPemiN5HkOjz/oC2pqRmu9zu9X9su/r6f0Ku6/X9tu5zuXjJZ3NYM8eS4773BGrnz1+mYxLJ9lxCZ7e83ee87RmpGJLSUSly7/PqmIyog4KRaMPLNR+ee2bF5UKTh7Zz7nr1kW41c8Up06d4lrClRz/P2/E/t590vneXdL3K65/Cx37BQUFcfXqVc5ZtAQGF+zzli/Fa6Vhv8KeQ195ftn3hZL7uybxaCEoXvTff/8pgLJly5Yc948dO1a5884789zHz89P+frrr3PcN3v2bKVixYp5bh8TE6MA8iM/8iM/8iM/8iM/Jf4nJibGZTFXaeGJeFRRJCaVH/mRH/mRH/mRn9LxI/Fobl5vO+Bu48ePz1GZcPXqVapXr86+ffsoU6aMF2cmiio5OZkGDRqwf/9+goPzv3xGFD9yDn2bnD/fJ+fQ9127do1GjRoRHx+f4/LQvKoMRPEgMWnJIu+jvk/Ooe+Tc+j75Bz6NolHC86rydfy5cuj0Wi4cOFCjvsvXLhAREREnvtEREQUavsblTtHRUXlKIsWviMpyd4uoXLlynIOfZScQ98m58/3yTn0fY7zFhYWVqBzWJSYq7TwRDwKEpOWNPI+6vvkHPo+OYe+T86hb5N4tOC8uoyhTqfj9ttvZ926dc77bDYb69ato3Xr1nnu07p16xzbA6xZs+aG2wshhBBClHZFiblKC4lHhRBCCCHcrzTHo15vOzB69GgGDBhAixYtuPPOO5k1axapqanOlc+eeuopKleuzLRp0wB48cUX6dChAzNmzOC+++5jyZIl7Ny5k08//dSbT0MIIYQQoljLL+YqzSQeFUIIIYRwv9Iaj3o9+dq/f38uXbrEhAkTOH/+PE2bNmX16tWEh4cDcOrUKdTqrALdNm3a8PXXX/P666/z6quvUrt2bZYvX06jRo0KNJ5erycmJkZ6UPgwOYe+T86hb5Pz5/vkHPq+opzD/GKu0szT8SjI/0NfJ+fP98k59H1yDn2fnEPfJvFowakURVG8PQkhhBBCCCGEEEIIIYQoabza81UIIYQQQgghhBBCCCFKKkm+CiGEEEIIIYQQQgghhBtI8lUIIYQQQgghhBBCCCHcQJKvQgghhBBCCCGEEEII4QYlMvk6e/ZsoqOjMRgMtGzZku3bt990+++//5569ephMBho3Lgxq1at8tBMxY0U5hx+9tln3HXXXZQtW5ayZcvSpUuXfM+5cL/C/j90WLJkCSqVij59+rh3guKmCnv+EhMTGTZsGJUqVUKv11OnTh15L/Wywp7DWbNmUbduXfz9/YmKimLUqFEYjUYPzVZkt3HjRnr16kVkZCQqlYrly5fnu09sbCzNmzdHr9dTq1YtFi1a5PZ5ivxJTOrbJB71fRKP+j6JSX2bxKO+TWJSF1JKmCVLlig6nU75/PPPlX///VcZPHiwEhoaqly4cCHP7Tdv3qxoNBrlnXfeUfbv36+8/vrrip+fn/LPP/94eObCobDn8LHHHlNmz56t7NmzRzlw4IAycOBApUyZMsqZM2c8PHPhUNhz6BAfH69UrlxZueuuu5TevXt7ZrIil8Kev4yMDKVFixZKjx49lD///FOJj49XYmNjlbi4OA/PXDgU9hwuXrxY0ev1yuLFi5X4+Hjlt99+UypVqqSMGjXKwzMXiqIoq1atUl577TVl6dKlCqAsW7bsptsfP35cCQgIUEaPHq3s379f+eijjxSNRqOsXr3aMxMWeZKY1LdJPOr7JB71fRKT+jaJR32fxKSuU+KSr3feeacybNgw522r1apERkYq06ZNy3P7hx9+WLnvvvty3NeyZUvlueeec+s8xY0V9hxez2KxKMHBwcoXX3zhrimKfBTlHFosFqVNmzbK/PnzlQEDBkiw60WFPX+ffPKJUqNGDcVkMnlqiiIfhT2Hw4YNUzp37pzjvtGjRytt27Z16zxF/goS6L788stKw4YNc9zXv39/pVu3bm6cmciPxKS+TeJR3yfxqO+TmNS3STxaskhMemtKVNsBk8nErl276NKli/M+tVpNly5d+Ouvv/Lc56+//sqxPUC3bt1uuL1wr6Kcw+ulpaVhNpsJCwtz1zTFTRT1HE6ePJmKFSsyaNAgT0xT3EBRzt/PP/9M69atGTZsGOHh4TRq1IipU6ditVo9NW2RTVHOYZs2bdi1a5fzUrDjx4+zatUqevTo4ZE5i1sjsUzxIzGpb5N41PdJPOr7JCb1bRKPlk4Sy9yY1tsTcKXLly9jtVoJDw/PcX94eDgHDx7Mc5/z58/nuf358+fdNk9xY0U5h9cbN24ckZGRuf7TC88oyjn8888/WbBgAXFxcR6YobiZopy/48eP88cff/D444+zatUqjh49ytChQzGbzcTExHhi2iKbopzDxx57jMuXL9OuXTsURcFisTBkyBBeffVVT0xZ3KIbxTJJSUmkp6fj7+/vpZmVXhKT+jaJR32fxKO+T2JS3ybxaOkkMemNlajKVyGmT5/OkiVLWLZsGQaDwdvTEQWQnJzMk08+yWeffUb58uW9PR1RBDabjYoVK/Lpp59y++23079/f1577TXmzp3r7amJAoqNjWXq1KnMmTOH3bt3s3TpUlauXMmbb77p7akJIYTPkXjU90g8WjJITOrbJB4VJVmJqnwtX748Go2GCxcu5Lj/woULRERE5LlPREREobYX7lWUc+jw3nvvMX36dNauXcttt93mzmmKmyjsOTx27BgnTpygV69ezvtsNhsAWq2WQ4cOUbNmTfdOWjgV5f9gpUqV8PPzQ6PROO+rX78+58+fx2QyodPp3DpnkVNRzuEbb7zBk08+yTPPPANA48aNSU1N5dlnn+W1115DrZbvaouzG8UyISEhpbrCwJskJvVtEo/6PolHfZ/EpL5N4tHSSWLSGytRv706nY7bb7+ddevWOe+z2WysW7eO1q1b57lP69atc2wPsGbNmhtuL9yrKOcQ4J133uHNN99k9erVtGjRwhNTFTdQ2HNYr149/vnnH+Li4pw/999/P506dSIuLo6oqChPTr/UK8r/wbZt23L06FHnhxSAw4cPU6lSJQlyvaAo5zAtLS1XQOv44KIoivsmK1xCYpniR2JS3ybxqO+TeNT3SUzq2yQeLZ0klrkJ76735XpLlixR9Hq9smjRImX//v3Ks88+q4SGhirnz59XFEVRnnzySeWVV15xbr9582ZFq9Uq7733nnLgwAElJiZG8fPzU/755x9vPYVSr7DncPr06YpOp1N++OEH5dy5c86f5ORkbz2FUq+w5/B6srqsdxX2/J06dUoJDg5Whg8frhw6dEhZsWKFUrFiReWtt97y1lMo9Qp7DmNiYpTg4GDlm2++UY4fP678/vvvSs2aNZWHH37YW0+hVEtOTlb27Nmj7NmzRwGUmTNnKnv27FFOnjypKIqivPLKK8qTTz7p3P748eNKQECAMnbsWOXAgQPK7NmzFY1Go6xevdpbT0EoEpP6OolHfZ/Eo75PYlLfJvGo75OY1HVKXPJVURTlo48+UqpWrarodDrlzjvvVLZu3ep8rEOHDsqAAQNybP/dd98pderUUXQ6ndKwYUNl5cqVHp6xuF5hzmG1atUUINdPTEyM5ycunAr7/zA7CXa9r7Dnb8uWLUrLli0VvV6v1KhRQ5kyZYpisVg8PGuRXWHOodlsViZOnKjUrFlTMRgMSlRUlDJ06FAlISHB8xMXyvr16/P8u+Y4ZwMGDFA6dOiQa5+mTZsqOp1OqVGjhrJw4UKPz1vkJjGpb5N41PdJPOr7JCb1bRKP+jaJSV1HpShSvy2EEEIIIYQQQgghhBCuVqJ6vgohhBBCCCGEEEIIIURxIclXIYQQQgghhBBCCCGEcANJvgohhBBCCCGEEEIIIYQbSPJVCCGEEEIIIYQQQggh3ECSr0IIIYQQQgghhBBCCOEGknwVQgghhBBCCCGEEEIIN5DkqxBCCCGEEEIIIYQQQriBJF+FEEIIIYQQQgghhBDCDST5KoQQBTBw4ED69OnjvN2xY0dGjhzp8XnExsaiUqlITEz0+NhCCCGEEMK7JCYVQgjfI8lXIYTPGjhwICqVCpVKhU6no1atWkyePBmLxeL2sZcuXcqbb75ZoG09HZxGR0c7X5eAgAAaN27M/PnzPTK2EEIIIURpIzFp3iQmFUIIO0m+CiF8Wvfu3Tl37hxHjhzhpZdeYuLEibz77rt5bmsymVw2blhYGMHBwS47nqtNnjyZc+fOsW/fPp544gkGDx7Mr7/+6u1pCSGEEEKUSBKT5k1iUiGEkOSrEMLH6fV6IiIiqFatGs8//zxdunTh559/BrIuy5oyZQqRkZHUrVsXgNOnT/Pwww8TGhpKWFgYvXv35sSJE85jWq1WRo8eTWhoKOXKlePll19GUZQc415/iVdGRgbjxo0jKioKvV5PrVq1WLBgASdOnKBTp04AlC1bFpVKxcCBAwGw2WxMmzaN6tWr4+/vT5MmTfjhhx9yjLNq1Srq1KmDv78/nTp1yjHPmwkODiYiIoIaNWowbtw4wsLCWLNmTSFeWSGEEEIIUVASk+ZNYlIhhJDkqxCihPH3989RTbBu3ToOHTrEmjVrWLFiBWazmW7duhEcHMymTZvYvHkzQUFBdO/e3bnfjBkzWLRoEZ9//jl//vknV69eZdmyZTcd96mnnuKbb77hww8/5MCBA8ybN4+goCCioqL48ccfATh06BDnzp3jgw8+AGDatGl8+eWXzJ07l3///ZdRo0bxxBNPsGHDBsAekD/wwAP06tWLuLg4nnnmGV555ZVCvR42m40ff/yRhIQEdDpdofYVQgghhBBFIzFpThKTCiFKNUUIIXzUgAEDlN69eyuKoig2m01Zs2aNotfrlTFjxjgfDw8PVzIyMpz7fPXVV0rdunUVm83mvC8jI0Px9/dXfvvtN0VRFKVSpUrKO++843zcbDYrVapUcY6lKIrSoUMH5cUXX1QURVEOHTqkAMqaNWvynOf69esVQElISHDeZzQalYCAAGXLli05th00aJDy6KOPKoqiKOPHj1caNGiQ4/Fx48blOtb1qlWrpuh0OiUwMFDRarUKoISFhSlHjhy54T5CCCGEEKJoJCbNm8SkQghhp/Ve2lcIIW7dihUrCAoKwmw2Y7PZeOyxx5g4caLz8caNG+f4dn3v3r0cPXo0V28so9HIsWPHuHbtGufOnaNly5bOx7RaLS1atMh1mZdDXFwcGo2GDh06FHjeR48eJS0tja5du+a432Qy0axZMwAOHDiQYx4ArVu3LtDxx44dy8CBAzl37hxjx45l6NCh1KpVq8DzE0IIIYQQBScxad4kJhVCCJDkqxDCp3Xq1IlPPvkEnU5HZGQkWm3Ot7XAwMAct1NSUrj99ttZvHhxrmNVqFChSHPw9/cv9D4pKSkArFy5ksqVK+d4TK/XF2ke2ZUvX55atWpRq1Ytvv/+exo3bkyLFi1o0KDBLR9bCCGEEELkJDFp3iQmFUII6fkqhPBxgYGB1KpVi6pVq+YKcvPSvHlzjhw5QsWKFZ2BoOOnTJkylClThkqVKrFt2zbnPhaLhV27dt3wmI0bN8Zmszn7Yl3PUeVgtVqd9zVo0AC9Xs+pU6dyzSMqKgqA+vXrs3379hzH2rp1a77P8XpRUVH079+f8ePHF3pfIYQQQgiRP4lJ8ycxqRCitJLkqxCiVHn88ccpX748vXv3ZtOmTcTHxxMbG8uIESM4c+YMAC+++CLTp09n+fLlHDx4kKFDh5KYmHjDY0ZHRzNgwAD+97//sXz5cucxv/vuOwCqVauGSqVixYoVXLp0iZSUFIKDgxkzZgyjRo3iiy++4NixY+zevZuPPvqIL774AoAhQ4Zw5MgRxo4dy6FDh/j6669ZtGhRkZ73iy++yC+//MLOnTuLtL8QQgghhHAdiUklJhVClB6SfBVClCoBAQFs3LiRqlWr8sADD1C/fn0GDRqE0WgkJCQEgJdeeoknn3ySAQMG0Lp1a4KDg+nbt+9Nj/vJJ5/Qr18/hg4dSr169Rg8eDCpqakAVK5cmUmTJvHKK68QHh7O8OHDAXjzzTd54403mDZtGvXr16d79+6sXLmS6tWrA1C1alV+/PFHli9fTpMmTZg7dy5Tp04t0vNu0KAB99xzDxMmTCjS/kIIIYQQwnUkJpWYVAhReqiUG3XrFkIIIYQQQgghhBBCCFFkUvkqhBBCCCGEEEIIIYQQbiDJVyGEEEIIIYQQQgghhHADSb4KIYQQQgghhBBCCCGEG0jyVQghhBBCCCGEEEIIIdxAkq9CCCGEEEIIIYQQQgjhBpJ8FUIIIYQQQgghhBBCCDeQ5KsQQgghhBBCCCGEEEK4gSRfhRBCCCGEEEIIIYQQwg0k+SqEEEIIIYQQQgghhBBuIMlXIYQQQgghhBBCCCGEcANJvgohhBBCCCGEEEIIIYQbSPJVCCGEEEIIIYQQQggh3ECSr0IIIYQQQgghhBBCCOEGknwVQgghhBBCCCGEEEIIN5DkqxBCCCGEEEIIIYQQQriBJF+FEEIIIYQQQgghhBDCDST5KoQQQgghhBBCCCGEEG4gyVchhBBCCCGEEEIIIYRwA0m+CiGEEEIIIYQQQgghhBtI8lUIIYQQQgghhBBCCCHcQJKvQgghhBBCCCGEEEII4QaSfBVCCCGEEEIIIYQQQgg3kOSrEEIIIYQQQgghhBBCuIEkX4UQQgghhBBCCCGEEMINJPkqhBBCCCGEEEIIIYQQbiDJVyGEEEIIIYQQQgghhHADSb4KIYQQQgghhBBCCCGEG0jyVQghhBBCCCGEEEIIIdxAkq9CCCGEEEIIIYQQQgjhBpJ8FUIIIYQQQgghhBBCCDeQ5KsQQgghhBBCCCGEEEK4gSRfhRBCCCGEEEIIIYQQwg0k+SqEEEIIIYQQQgghhBBuIMlXIYQQQgghhBBCCCGEcANJvgohhBBCCCGEEEIIIYQbSPJVCCGEEEIIIYQQQggh3ECSr0IIIYQQQgghhBBCCOEGknwVQgghhBBCCCGEEJSCaWgAAQAASURBVEIIN/Bq8nXjxo306tWLyMhIVCoVy5cvz3ef2NhYmjdvjl6vp1atWixatMjt8xRCCCGEECWTxKNCCCGEEMKdvJp8TU1NpUmTJsyePbtA28fHx3PffffRqVMn4uLiGDlyJM888wy//fabm2cqhBBCCCFKIolHhRBCCCGEO6kURVG8PQkAlUrFsmXL6NOnzw23GTduHCtXrmTfvn3O+x555BESExNZvXq1B2YphBBCCCFKKolHhRBCCCGEq2m9PYHC+Ouvv+jSpUuO+7p168bIkSNvuE9GRgYZGRnO2xaLhQMHDhAVFYVaLS1vhRBCCOF7bDYbFy5coFmzZmi1PhXO+byixKMgMakQQgghShaJRwvOp16d8+fPEx4enuO+8PBwkpKSSE9Px9/fP9c+06ZNY9KkSZ6aohBCCCGEx2zfvp077rjD29MoVYoSj4LEpEIIIYQomSQezZ9PJV+LYvz48YwePdp5+/Tp0zRq1IiNGzcSFRXlsnH++e8azy+Oo1IZA98/19Jlx83PkMV72PdfEiPursHDt7vu+RRnZrOZjRs30r59e/z8/G75eAs3n2DB5pP0alKJcd3q5Lv9+GX72HTkCi91rUXfZpVvefxb1feTv7iUbGJQ22o83Tba29MpEFefQ+FZcv58n5zD4stsNWNVrBi0hpwPHI9Fs+Z1VBnXUHSBnGr4Au2eej1XElAUX56KSYVnyPuo75Nz6PvkHBac2Wqj04xNAHz59O3UqBDk5RnZyTn0MckXUP82DvXZXQCcjuhGm3E/SjxaAD6VfI2IiODChQs57rtw4QIhISE3rDLQ6/Xo9Xrn7TJlygAQFRVFdHS0y+aWqruGNuQM6mC9S4+bH3XQabQhOkLKR3p0XG8ym83s37+f6Ohol7xB+x8wog1JJbJylQK9hpGVr6G9oMJQNsLrr7nFauOa+l+0IWAIC/f6fArK1edQeJacP98n57B4On3tNI//+Dj1y9dn/v3z7XdaTLBuEvz1MeiB6Obw0EKsSWrgdblc3QuKEo+C52JS4RnyPur75Bz6PjmHBZeSYUEbUh6AipFRRFcu4+UZ2ck59CFH1sKvz0LaFSgfAr0+wBLcAsb9KPFoAfjUK9S6dWvWrVuX4741a9bQunVrL80oi16rASDDYvPouOlmKwAmD49bkqSbLAAE6DQF2j7E3/6dRZLR7LY5FdTF5AxsmUvmpWZYvDsZIYQQRfbrkV9pNq8ZW05v4Yf9P3Am6QwknISF99oTrwAtn4dBv0NYDe9OtpQrzvGoEEIIkZeMzLwBeD5nIXyc1QxrYmDxg/bEa8Rt8NxGaNzP2zPzKV5NvqakpBAXF0dcXBwA8fHxxMXFcerUKcB+edZTTz3l3H7IkCEcP36cl19+mYMHDzJnzhy+++47Ro0a5Y3p56DX2l/KDLOHk68mSb7eKkcC2+BXsORrsMH+jVxyMUi+nrtmdP47NcN6ky2FEEIURxabhdfWvUaPr3twJf0Kt1e6nd3P7abKf3Ew7y74bycYykD/xXDvdNDq8z2mKJySFI8KIYQQecmecM2wyOdGUTAJ5//mxKyGsHmW/Y47BsOgNVCuplfn5Yu82nZg586ddOrUyXnb0QdrwIABLFq0iHPnzjkDX4Dq1auzcuVKRo0axQcffECVKlWYP38+3bp18/jcr+dIvpqsXqp89fC4JUlaZgK7wJWvhszK13TvV5qeu5bu/LdUvgohhG85m3yWx358jA0nNwAw7I5hzOg8Ff36KbBtrn2jyi2g3+dQtpoXZ1qylaR4VAghhMhL9uSrFG6J/KSYUli14gW6/L2UaCBFpSaw30JUDft4eWa+y6vJ144dO6Ioyg0fX7RoUZ777Nmzx42zKhpH2wGrTcFitaHVeKaoWNoO3Lp0Z/JVjdlsxmq9+TeB5QwqKgdr0ChmjEbjTbd1t4SkVCoH23/3dCqL1+dTUGazGa1Wi9FozPf1FsWPnD/P0mg0aLVaVCqVt6ciXGjd8XU8tvQxLqZeJFgXzPz75/NwpRbwRS84F2ffqM0LcHcMaKQHmjuVpHhU+D5FUbBYLPL31QMknvF9cg4LzphudH5utJgyivS5UWLSks9kNbFgxyeo1k1miNle3PWvVselHu/SoUFvL8/Ot/nUglvFmd4vK9maYfFM8tVqU5xJV+nbUnRpJithBjWRmjSOHj2a7/bVdFYmdqqIXqsmPj7eAzO8sVr+ZiZ2qgiArhjMp6AURSEiIoLTp0/LH28fJOfP8wICAqhUqRI6nc7bUxG3yGqz8ubGN5m8YTIKCk3Cm/D9Q99T+/w+mNcBMpLAvyz0nQd1pJJSiNLEZDJx7tw50tLSvD2VUkHiGd8n57DgTBab83NjWds14uNTinQciUlLJpti45t/vmHe2ld5N+kKLbEn6g/W6kz9R76hodbg5Rn6Pkm+uohOkzP5GuiBlmzp2ZpmS+Vr0RktVl5pF0a5AA2RlcLR6XQ3/eOdmmFGk5COTquhevlAD840t/8S0gjIbDeg02ioXsG78ykom81GSkoKQUFBsjKiD5Lz5zmKomAymbh06RLx8fHUrl1bXnMfdiHlAo8vfZx18fbFmgY3H8wHXd7Gf92bsHOBfaOoVtBvAZSp4sWZCiE8zWazER8fj0ajITIyMt94VNw6iWd8n5zDgkszWeCq/YudiBADZQIKlzyVmLRksNoUzibaWxeqVKACYk+sZ/rmadS5vI+fUQhFg1Hrj6nnbKrU743RBlqLDZ1WzvetkOSri6jVKvw0KsxWxWOJUMfl8iA9X2+Fv8pG2QAtFcMjKFMmJN/tbWotqmQraNQYDN79BkjRWFA53gSLwXwKymazYTKZMBgM8kfbB8n58yx/f3/8/Pw4efKk83UXvmfDiQ08+uOjnEs5R4BfAPN6zuOJyFawqBdc+AeAi02GsaHyYIwHrDzZyssTFkJ4lMlkwmazERUVRUBAgLenUypIPOP75BwWnBkzKq29aEer12MwFL5aTGJS32U0W/lx9xnmbTjOqas5r67QYWa8NpKntfZ4dLetFi+kvMB/SwzAbwDcd1slZj/W3NPTLlEk+epCeq0Gs9XisdUDjTkqX6XHTVFlWK2ACnUBW0VoMqsQrLYb94fzFHO2pLvtJv3qhBC+TT5Q+C6bYmP6n9N5Y/0b2BQbDco35JPu31DuyDZMP92FzppGgqoMIzOGsGFbE2A/FYL1PNlKFtgSojSS93shhDtk/6h4Kx8b5T3Kt6RkWPh620nmb4rnYnIGAFo12DBjsVmJVl1itt8cGqtPAjDX0pP3LA9juS5VqJYrMW6ZJF9dSK9Vk5Lhuf6radkqX81WSbwVlSOJXdA3FI3avp1NUVAUxWuXhCmKfXE3B5sNr85HCCFETpfTLtP/mxFsP3GFMrZniApojf5SGP8tfIP22vUAbLXVZ4RpOBcpS9kAP+pXCqFeRAhmqw0/Dy3eKYQQQoiSLfvCkjdbZFKUDAmpJhZuOcEXW05wLd0MQIVgLSFh24m9MBWbykh/dCxUBeFvs4B/GPSdy3O17+FZxZ7rsCmOnIe9RYG4NZJ8dSFHD4wMs4faDkjPV5cwZp4vdQHfUNTZNrTaFLQa77wTma0K2f9sKsgboxBCFAdXU018EPsni/46gMryOOUy7y+f8h+z/V6lnvY0NlT8Xu4pTjYaxjuRZalfKYSKwXr5Ak0IIYQQLpc9WyC515Lr3LV0PtsYzzfbTznzRVXD9IRV2Mmq05MxX0zHAPwU2pB7Ek6DYoGqreHBBVCmMirs+QQ1Eo+6mpRUuJA+M/lqsnqmBUCOnq+SfC0SRVEwZrZsKOgHXrVK5ayStXrxL5ej5UD2yqhbbT0QGxuLSqUiMTGxwPtMnDiRpk2b3tK4hdGxY0dGjhzpsfGEyI/8Tgqw/x3+7d/zPPvlTlq89TtfbEpHZYkGrDSJ0vNR/QP8FjCBeurTKIEVUT+1nO4vfMhznerSsW5FwkMMkngVQohMEpMKUXg3+53MXu1aDLrnCReLv5zKuB/+pv076/l8czzpZiv1KgXSockRdpv78tOp8ZiVdAZWacuVsKb2xCsquOslGLACylT29lMo8ST56kJ6rQbwXOVr9p6vGbLgVpFkWGw4ykcL08fE2XrAS3+55s6dS0T5slgsFnQaNWqVirTUFPwNejp27JhjW0fweuzYsXyP26ZNG86dO0eZMmVcOl9PBqeLFi0iNDTUI2PlpaDPNT4+nscee4zIyEgMBgNVqlShd+/eHDx40P2T9ALH76Hjp0KFCvTo0YN//vnH21O7ZUuXLuXNN9/09jSEFyiKwt9nEon5aR8tp67lua928fv+C9gUFRmqo1SvupONo5rxU+SP9Ip/E601Hap3QDXkT6jR0dvTF0KIWzZ37lyCg4OxWCzO+1JSUvDz85OYVGLSYqm0xqTZP7bmvH5S+LJ/z15j2Ne7uXtGLN/uPI3ZqtAiOpQ+rc+w09iPLw+PItWSQovIFvzT9g0Wnj9OwNXjEFAenvgR7p4AGrkg3hPkVXYhvV9m2wEv9HyVyteiyf4aFrTtgH1b7y661alTJ1JSUtj/9x7at21LhsXG7u1/ER4RwbZt2zAajc7VJ9evX0/VqlWpWbNmvsfV6XRERES4e/qlntlspmvXrtStW5elS5dSqVIlzpw5w6+//lqoCg93MZlM6HQ6txz70KFDhISEcPbsWcaOHct9993H0aNH3TYe2F9vPz8/tx0/LCzMbccWxdOFJCPL9vzHj7vOcORiStYD6mtcU6/F7LeJGfeN4dmofqi+fwAuHwaVGjq+CneNBrXGe5MXQggXcsSkO3fupFWrVgBs2rSJCIlJfYLEpKUnJnXVgluieDh5JZXJv+xn3cGLzvs61a1AdOXDLPj3eX6MOw1A3XJ1md5+Ar3jt6D68wP7htF3wQOfQUglb0y91JLKVxdytB3IsHio7UCOnq+eGbOkSTPZv6VXqXK2HVAUhVRT6g1/MqxppJlTScq48TZF+Slo8/O6desSHhHBjr/+xE+rQq2GHX/9yX09e1G9enW2bt3q3DY2NpZOnToBYLPZmDZtGtWrV8ff358mTZrwww8/5Nj2+ku8PvvsM6KioggICKBv377MnDkzz2/xv/rqK6KjoylTpgyPPPIIycnJAAwcOJANGzbwwQcfOL9hPnHiBAD79u3j3nvvJSgoiPDwcJ588kkuX77sPGZqaipPPfUUQUFBVKpUiRkzZhTo9bmZxMREnnnmGSpUqEBISAidO3dm7969zsePHTtG7969CQ8PJygoiDvuuIO1a9fmOMacOXOoXbs2BoOB8PBw+vXrl+9zze7ff//l2LFjzJkzh1atWlGtWjXatm3LW2+95fzgArB9+3aaNWuGwWCgRYsWLFu2DJVKRVxcHJB3RcXy5ctz/C4X5PlER0fz5ptv8tRTTxESEsKzzz4LwJ9//sldd92Fv78/UVFRjBgxgtTUVOd+n3zySZ6vw81UrFiRiIgImjdvzsiRIzl9+nSOyor8xjx37hz33Xcf/v7+VK9ena+//pro6GhmzZrl3EalUvHJJ59w//33ExgYyJQpUwD46aefaN68OQaDgRo1ajBp0iRnpY6iKEycOJGqVaui1+uJjIxkxIgRzmPe6JxD7sqShIQEnnrqKcqWLUtAQAD33nsvR44ccT7uOG+//fYb9evXJygoiO7du3Pu3Ll8Xz/hPVabws97z/LU59tpPW0d0389yJGLKei1aupWSeaK/k1O6p6kXMWNbBr8Lc+pDKg+62xPvAZXggG/QIexkngVQhRYfvGoO38KE5NWqlSJ2NhY532xsbH07t272MekGo2GU6dOARKTSkxa8mPSauFlGfpkP07GH3O2qpOY1PdYbQrzNx2n26yNrDt4EbUKet1WiTG9zGxLG8jEv57kdNJpKgdXZn6v+ex76Af6bPoQ1Z6vABV0eAWe+kkSr14gla8u5Fxwy0NVqDmSr9J2oEgcfXOv/xYizZxG0LQgj88nZXwKgbrAAm3bqm17dmz5E7/MtgM7tvzJuJfHokZh/fr1dOzYkfT0dLZt28b//vc/AKZNm8b//d//MXfuXGrXrs3GjRt54oknqFChAh06dMg1xubNmxkyZAhvv/02999/P2vXruWNN97Itd2xY8dYvnw5K1asICEhgYcffpjp06czZcoUPvjgAw4fPkyjRo2YPHkyAOXKlePs2bN06dKFZ555hvfff5/09HTGjRvHww8/zB9//AHA2LFj2bBhAz/99BMVK1bk1VdfZffu3bfUz+uhhx7C39+fX3/9lTJlyjBv3jzuvvtuDh8+TFhYGCkpKfTo0YMpU6ag1+v58ssv6dWrF4cOHaJq1ars3LmTESNG8NVXX9GmTRuuXr3Kpk2bAPJ8rhUqVMg1hwoVKqBWq/nhhx8YOXIkGk3uZExKSgo9e/aka9eu/N///R/x8fG8+OKLhX6++T0fh/fee48JEyYQExMD2M9p9+7deeutt/j888+5dOkSw4cPZ/jw4SxYsIA9e/bw4osv5vk6FMS1a9dYsmQJgLPC4GZjLly4EICnnnqKy5cvExsbi5+fH6NHj+bixYu5jj9x4kSmT5/OrFmz0Gq1bNq0iaeeeooPP/yQu+66i2PHjjkD+piYGH788Ufef/99lixZQsOGDTl//rzzA9DNznleBg4cyJEjR/j5558JCQlh3Lhx9OjRg/379zurHdLS0njvvff46quvUKvVPPHEE4wZM4bFixcX+DUUnpNusjL86905qgtaVCtLj9vK8fPJSfx05BtQw4P1H2RBtw8oszYG/vnevmGtLtB3HgSW99LshRC+ylvxKBQuJu3UqRPr16/nlVdeAewVri+//DJWq7VYx6Q2mw29Xk9iYiKdO3eWmFRi0hIdk5pUeia8/irDn3qY9Vt3O7eRmNR3HLmQzMs//s2eU4kAtK5Rjl53pPLBruf5eO12AML8w3i13asMvWMo/vuWwvyuYE6DoHB7tWuN3O+vwkOUUub06dMKoMTHx7v82E8v3K5UG7dC+XbHKZcfOy/zNhxVqo1boVQbt0K5c8oaj4xZHJhMJmX58uWKyWS65WPFnUpQ2rz1q/LHX7uV9PR05/0pGSkKE/H4T0pGSoHnPmXGR4p/QKByOSlNiTt2VtFqtcrRE2eUr7/+Wmnfvr2iKIqybt06BVBOnjypGI1GJSAgQNmyZUuO4wwaNEh59NFHFUVRlPXr1yuAkpCQoCiKovTv31+57777cmz/+OOPK2XKlHHejomJUQICApSkpCTnfWPHjlVatmzpvN2hQwflxRdfdN62Wq3Ka6+9pnTt2jXHsR3/Pw8dOqQkJycrOp1O+e6775yPX7lyRfH3989xrOstXLgwx/yy27RpkxISEqIYjcYc99esWVOZN2/eDY/ZsGFD5aOPPlIURVF+/PFHJSQkJMfzze7653ojH3/8sRIQEKAEBwcrnTp1UiZPnqwcO3bM+fi8efOUcuXK5fi9/OSTTxRA2bNnzw2f67Jly5T83tqzPx9FUZRq1aopffr0ybHNoEGDlGeffTbHfZs2bVLUarWSmpqqfPnllzd9Ha7n+N0KDAxUAgMDFezdlpX777+/QGOmp6crBw4cUABlx44dzsePHDmiAMr777/vvA9QRo4cmeM4d999tzJ16tQc93311VdKpUqVFEVRlBkzZih16tTJ832lMOf88OHDCqBs3rzZ+fjly5cVf39/5+/ywoULFUA5evSoc5vZs2cr4eHheR5fURQlPT1d2b9/f47fh1vhyvfRku5qSobSd/afSrVxK5Q6r61S3vvtoBJ/KUXZdXaXUvODmgoTUfwm+ykfbv1QsZ2NU5QPmytKTIiiTCyrKJtmKorV6pZ5xcfHK4By+vRptxxfuJ87Y1Lhfq5+H83rfd5b8WhhY9LPPvtMCQwMVMxms5KUlKRotVrl4sWLxT4mtVqtSkJCgjJ58mTlnnvuyXFsiUklJi1pMenZxDRlw9/HFIPBX5mz4CtFUSQm9RUmi1X5cO1hpfarq5Rq41YojSasVqb9tlHp+uU9zvfsgCkByuvrXlcS0xMVxZisKEufs8ejMSGK8sX9ipJ8wS1zk3i04KTy1YX0nq58NWWNIz1fi8ZRPXz9WlsBfgGkjE/JYw+7/xLTuJpqomKIgfBgg8vmE+AXUOBtm7dqS3paKn/v2Un8f5eoWqMWZcvbqwWefvppjEYjsbGx1KhRg6pVq/Lvv/+SlpZG165dcxzHZDLRrFmzPMc4dOgQffv2zXHfnXfeyYoVK3LcFx0dTXBwsPN2pUqV8vzmN7t9+/YRGxtLUFDuio5jx46Rnp6OyWSiZcuWzvvDwsKoW7fuTY97M3v37iUlJYVy5crluD89Pd25+ENKSgoTJ05k5cqVnDt3DovFQnp6uvOytK5du1KtWjVq1KhB9+7d6d69O3379iUgoODnDmDYsGE89dRTxMbGsnXrVr7//numTp3Kzz//TNeuXTlw4AC33Xabs08aQOvWrQv9nPN7Pg4tWrTIcXvv3r38/fffOb71VhQFm81GfHw8HTt2LNLrsGnTJgICAti6dStTp05l7ty5BR7z8OHDaLVamjdv7ny8Vq1alC1bNtc4eT2fzZs3Oy/3ArBarRiNRtLS0njooYeYNWuW8/n06NGDXr16odVqC3XODxw4gFarzfF7W65cOerWrcuBAwec9wUEBOToeVeQ/zPCc2w2G4mJiZy7ls7Qxbs5fimVEIOWD/s1o2lUKIvi5jJ+3XjMVjNVQqrw/ZPf0erCv/bqAmsGhFSGfp9D1Vb5DyaEEDeQXzzq7rELqmPHjqSmprJjxw4SEhKoU6eOs4LVF2LSvXv3sn79eolJJSYt8Ji+GJMqCoSWDaNazVocOZzVXkFi0uJt33/XGPvD3xw4lwRAyxoBZAR9yfi/FgGgVWt57vbneL3960QERcCFf+H7gdguHSLRqLKvNdBqGJjUcPXqDccJDQ1FrZaupO4kyVcXciZfzd7o+SrJ16JwtB24fq0tlUp100utgvVqjKYMDBo9gTp/N84wbzZFIbJqdcIrRfLnxo2cOX+JFi3b2O+PjCQqKootW7awfv16OnfuDNgDHoCVK1dSuXLlHMfT6/W3NJ/rG8erVCpstpv/TjouYXrnnXdyPVapUiWOHj16S3O60ZjX9yVzcPSpGjNmDGvWrOG9996jVq1a+Pv7069fP0wmEwDBwcHs3r2b2NhYfv/9dyZMmMDEiRPZsWNHoVe0DQ4OplevXvTq1Yu33nqLbt268dZbb+X6MHIjarU6V082s9mc43Z+z8chMDDn73tKSgrPPfdcjh5TDlWqVMFoNLJz5042btxYqNehevXqhIaGUrduXS5evEj//v3ZuHFjvmNWrVqVw4cP3/T1yO/5TJo0iQceeCDXtgaDgaioKA4dOsTatWtZs2YNQ4cO5d1332XDhg0uPecOef2fuf5cCu9JTEzkje+2se5YCqkmK4F6Dd0bRbDxyDle/XURBy4fwMD9NCpbk7srtqLO2g/g1K/2net0hz6fQIAsxCaEuDX5xaPFRa1atahSpQrr168nISHB2TbAl2LSXr168fbbb+d6TGJSiUmv56sxqS3b+cl+piQmLZ6MZisfrDvCpxuPY7UplPHXUC1qBz+enoQVKypUPNb4MSZ1nETNsJr27PquL+DXl8FiJFEbzsyoCRgy6sKG4zcfKzWZ0T2bySLCbibJVxdy9Hz1VP9Vo/R8vWVpjuTr9aWv+dBkbm+1eecPk8VqH/eONnexaeMGLly6whPPDseWOZ/27dvz66+/sn37dp5//nkAGjRogF6v59SpU3n20spL3bp12bFjR477rr9dEDqdDqs155cSTZo0YeXKlURHR6PV5n4rqlmzJn5+fmzbts3ZByohIYHDhw8XeP7Xa968OefPn0er1RIdHZ3nNps3b2bgwIHO6oqUlJRcCxRotVq6dOlCly5diImJITQ0lD/++IMHHnggz+daECqVinr16rFlyxYA6tevz1dffZVjleDsi1aAvU9XcnIyqampzsDOsfBBYZ5PXpo3b87+/fupVatWrsdsNhtGo/Gmr0NBDBs2jGnTprFs2TL69u170zHB/vtosVjYs2cPt99+OwBHjx4lISGhQM/n0KFDNzw2gL+/v/ODx7Bhw6hXrx7//PMPzZs3L/BzrV+/PhaLhW3bttGmTRsArly5wqFDh2jQoEGBXhfhfXtOJbD6cBJWXRDly/nRt1ll0q1X+b9/v+dK+hW0/ga61OhK69BoUnd+C9ZVEOgHXSZB62G5L6cQQogSrlOnTsTGxpKQkMDYsWOd9/tCTNq8eXOWLl0qMWkmiUlLZkyqKJCYcJWTx45Sq069Ar0uwjt2nrjKyz/+zfFL9gXeosIvsTvlFf4+fQGA+2rfx5TOU2gS0cS+Q0Yy/DIS9mUuWlirC3SYjmF7AoEhoZ5/AiJPknx1Ib3W3qA8w+yZRGiayeL8t9mqoChKoZOIpZ3jNSzsy6ZR23eweelbQXNmsr11u/a89eoYzGYzLVq1dc6nQ4cODB8+HJPJ5FxVNjg4mDFjxjBq1ChsNhvt2rXj2rVrbN68mZCQEAYMGJBrnBdeeIH27dszc+ZMevXqxR9//MGvv/5a6N+z6Ohotm3bxokTJwgKCiI0NJRnnnmGr776ikcffZSXX36ZsLAwjh49ypIlS5g/fz5BQUEMGjSIsWPHUq5cOSpWrMhrr71WoMshrFZrroBPr9fTpUsXWrduTZ8+fXjnnXeoU6cOZ8+eZeXKlfTt25cWLVpQu3Ztli5dSq9evVCpVLzxxhs5KiZWrFjB8ePHad++PWXLlmXVqlXYbDbnpWfXP9ewsLBcc46LiyMmJoYnn3ySBg0aoNPp2LBhA59//jnjxo0D4LHHHuO1115j8ODBjB8/nhMnTvDee+/lOE7Lli0JCAjg1VdfZcSIEWzbto1Fixbl2Ca/53Mj48aNo1WrVgwfPpxnnnmGwMBA9u/fz5o1a/jwww9ZvXo1Fy5coEOHDnm+DgUREBDA4MGDiYmJoU+fPjcd8+OPP6ZevXp06dKFZ599lk8++QQ/Pz9eeukl/P398/2dnDBhAj179qRq1ar069cPtVrN3r172bdvH2+99RaLFi3CarU6X9P/+7//w9/fn2rVquV7zq9/vXv37s3gwYOZN28ewcHBvPLKK1SuXJnevXsX+LUR3rNm/wWe/2oXJqtC5RA9vZtGcuDKP6w6sgqLzUKIPoR+9R8kKvki7P4KjOkQVhkGfgVVWuQ/gBBClECdOnVi2LBhmM3mHAnJ4hyTBgQEoNVqGTp0KPPnz5eYVGLSEh2TJlu1TJn4OhUjKnF3t/sK/NoIz0nNsPDub4f44q8TKAoE6M1c0n7Mn0nrAGgb1ZZpd0/jrmp3Ze10bi98PxCuHgeVBu6eAG1GQGIikP+XAcJzpKmDC3m85+t1SV6pfi28rJ6vhax8VXu38tWRfG3brgPp6elE16hJuQoVcUynQ4cOJCcnU7duXSpVquTc78033+SNN95g2rRp1K9fn+7du7Ny5UqqV6+e5zht27Zl7ty5zJw5kyZNmrB69WpGjRqVo+dTQYwZMwaNRkODBg2oUKECp06dolKlSmzatAmr1co999xD48aNGTlyZI5+M++++y533XUXvXr1okuXLrRr18757fLNpKSk0KxZsxw/jkBv1apVtG/fnqeffpo6derwyCOPcPLkScLDwwGYOXMmZcuWpU2bNvTq1Ytu3brl6OcUGhrK0qVL6dy5M/Xr12fu3Ll88803NGzY8IbP9XpVqlQhOjqaSZMm0bJlS5o3b84HH3zApEmTeO211wAICgril19+4Z9//qFZs2a89tpruS6HCwsL4//+7/9YtWoVjRs35ptvvmHixIk5tsnv+dzIbbfdxoYNGzh8+DB33XUXzZo1Y8KECURGRgJQpkwZli1bdsPXoaCGDx/OgQMH+P777/MdE+DLL78kPDyc9u3b07dvXwYPHkxwcHC+v5PdunVjxYoV/P7779xxxx20atWK999/n2rVqgH28/rZZ5/Rtm1bbrvtNtauXcsvv/xCuXLl8j3n11u4cCG33347PXv2pHXr1iiKwqpVq3Jd1iWKnyXbT/HcVzvJsNioFuZPrybhrD62gp8P/YzFZqFWWC2GNBlA1OmdcHQtKDYIqwlPr5TEqxCiVOvUqRPp6enUqlXLGVNB8Y5Jw8PDOXPmDJGRkWzevFliUolJS3RM+sC9nVEU+PjL79DkUeEtvGvTkUt0m7WRRVvsiVer4U8OqZ7gsm0djSo24pdHf2HT05uyEq+KAts/s683cPU4hFSBp3+FdiNBercWSyqllDX0OHPmDFFRUcTHx9/wEo+ieve3g8xef4yn20YT06twb/ZF8cwXO1l74ILz9j8T7yHYUPI/3JvNZlatWkWPHj1uOZkxb8MxvvzzCO90q8TtjeoWOIBLSjdz4koq/n4aaocH57+Di11KzuDctXRCA3RUDQvgYrKR89eMlA3QERVWuCb7hTV48GAOHjzIpk2binwMm81GUlISISEh0ti7EE6cOEH16tXZs2cPTZs29do8itP5c7ynr127lrvvvturc3Eno9FIfHw81atXL/QHzby48n20JFAUhY//OMqMNfYebr3qBqPRprLy9G9cSruEChWdq3embWh1VPt/BuM1UKmhZmdSQ2oytFNtj/fJcrwfnD59mipVqnh0bOEa7oxJhfu5+n3U1e/zpcGtxqTFKZ7xNRKT5lbcY9Ljl1JIybBf9Wnw01CniJ9hJSZ1rWvpZqas3M93O8/Y79Bc5YLmfYyaPUSHRvNmpzd5tNGjaNSarJ2M1+DnF2D/T/bbde6FPnNyrDdw9epV5qw/WqC2A6lJiQztVKtIsazEowUnX3m4kE6T2XbAQ5WvxusW9pJFtwrP0fNVXcS2A1Yvtx3w09jnoVa5rw3Ce++9R9euXQkMDOTXX3/liy++YM6cOS4fR4iC+OOPP0hJSaFx48acO3eOl19+mejoaNq3b+/tqQkfZbUpTPrlX7786yQAwzrVJMg/ltd/2YBVryZYF8SD9R+kWvJF2LPYXu3qHwoNekNwJUhK9Or8hRCitJCYVBQnvhaTZv+UWLrK74qXi8lG/j59jb1nEok7nUjcqUSSMyyAjSTNChL9vqRCUAjvtv+Iwc0Ho9detwjhf7vhh6ch4QSotdB1MrQaKusN+ABJvrqQ3i9zwS0PJUGz93wFaTtQFLfadqAAbYrcIiv5av+d0ziTr64fa/v27bzzzjskJydTo0YNPvzwQ5555hnXDyREAZjNZl599VWOHz9OcHAwbdq0YfHixaXym3Jx64xmK6O/i2PVP+dRqeDVHrXZnvAu8/+YT7DtQWqVrc8Dte4l8FgsXMlc7bpCPajbHbRSmSaEEJ4kMakoTnwtJs2ecPXWuiWlTUqGhX/O2BOte0/bf85eM+bazqw6wxW/D9H5n2ZSm1cZ1XoUQbqgnBspCmybC7+/ATYzhFaFfougSv7tT0TxIMlXF/J6z1epfC0054JbhdzPUWlqtXlnoTOz1f4H05F8dVxl444etN99953LjymKJjo6mlLWKSaXbt260a1bN29PQ5QASUYzz365k63Hr6LTqBnboyIf//MQf1/4G4B2Ue3oUrkRqr3fQUYSqDX21WMjm1L4vxpCCCFulcSkxYfEpL4Xk2ZPuJbyU+cWFquNg+eTictMsu49k8iRiym5XmuVCqqG+ZGs7ONI8lpM6sOotGcZdufzjL9rPOUDyuc+eHoC/DQcDq6w367XE3rPtl+JJXyGJF9dSK/NbDtwXTsAd5G2A7fO0XagsLlTR+WrgoKieL7K35NtB4QQoqS5mGRkwMIdHDiXRJBey2N3JfPSxk4km5KpGFiRT3rOZv+fF1Dt/cb+CcW/LDTsA0Hh+R5bCCGEEKK4yf4xUUE+M7qSzabQZ85m9v2XlOuxyqH+3FalDE2iQokINfLjsVl8ve9zbIoNtZ+agU0GEtMxhqplquZ98DM74fun4dop0Ojgnilw52BpM+CDJPnqQjpPV76aciZfPTVuSWIsYtsBtcpe96Rg7/uq9mAVlE1RcrUdkOSrEEIUzInLqTyxYBtnEtIpH6SjXu0/eG3zdAA6VOvAkns/RrdsPPtPhoC/HsIbQJ1uoNHnc2QhhBBCiOJJkcpXt/nz6GX2/ZeETqOmZY0wmkaF0qRKKLdFlaFisIFLqZeYumkqL26ag8lqAuCB+g/wVqe3qF+hft4Htdlg62xYOxFsFihbHR5aCJHNPPfEhEtJ8tWFHG0HpOer73BWvhZyP5VKhVqtwmpTsNoU/DT57+MqlszzrFKp0GZW4Hq7B60QQviCA+eSeHLBdi6nZBAZ6kd68DssPrgWgFfbvcqk6veg/b9+XL14FtR9oO69UOk2pM2AEEIIIXyZ7bqer95onVdSLdlxCoBH74xiUu9GzvuTM5KZvOEd3tvyHsmmZAA6RXdi2t3TaFml5Y0PmHYVlg2BI7/ZbzfsC70+BEOI256DcD9JvrpQVs9XT7UdsGfaAnQa0kxWaTtQBI7kq7oIf3g02ZKvnpTV71Xl/IOZmXuVylchhLiBXSev8vTCHSQZLUSWVThgHUzi5VOU8y/HV72/4N7z/8JXfUCxQVhNiHwUImp6e9pCCCGEELfs+lYDCvLVsitcTslgzf4LAPS/w946IMOSwbxd83hr41tcSrsEQPNKzZl29zS61uh686T3yb/gx0GQ9J/9qqt7p8PtT0ubgRJAkq8upM8sf/TE5f8Wq81Z6VrG30+Sr0WUXsSerwAaL13qf33LAcjZdkC+xRRCiJw2HL7Ec1/txGi2ERaSyNb051BUqbSJasN33T+m8poYiN9g37jJY9D6Vdh8zruTFkIIIYRwkevrhRTJvrrE0t1nMFsVmlQpQ92IQL7c+yUT1k/g5LWTANQOq81bnd+iX4N+qFXqGx/IZoPN78MfU0CxQrla8NAiiGjsmSci3E6Sry6k03iu52t6tsW2yvj7ce6aUZKvReBo3VCUvzvqzHJTz1e+5pF8VWc9A6uioJXkqxBCALDi77OM+jYOs1VBF3CUONM4FFUGY1qPYVqN7mgXPwypF8EvAO6bAU0fg6tXvT1tIYQQQgiXUDILdK6/T7Kvt0ZRFJbsOA1A/aoJNJnbhH8v/QtAZHAkMR1ieLrp0/hp/G5+oJRLsOw5OLbOfrvxw9BzJuiD3Tl94WE3Sb2LwtL7ea7na7o5q2Iz2GDPoZul52uhOVo3FKVS1FH56s22Aw5qVVYLguLS91WlUrF8+XK3j7No0SJCQ0OdtydOnEjTpk2dtwcOHEifPn3cPo/soqOjmTVrlkfHFELk9s32U7zwzR7MVgWzbitHbGMI9Q/g54eX865fWbT/96A98VqxAQxeb0+8CiGEKFEkJp3l0TFF8ZPXhZoe/ghbIu04kcDxS6moVCbe2d2ffy/9S6ghlLe7vM2RF47w7O3P5p94PfEnzG1nT7xq/eH+j+GBTyXxWgJJ8tWFPNnz1WjK7Pfqp0HnWOhLkq+F5qx8LUrbAUflq5fbDvz1119oNBqGPfUwULg2CN4OyM6fP88LL7xAjRo10Ov1REVF0atXL9atW1fkY44ZM+aW9i+M64Nshx07dvDss896ZA5CiLzN3XCM8Uv/QVEgWfMrZ9VTuaNyM/Y+vppeWz+FDW8DCjR/Cp5ZBxXreXvKQgjh0xwx6X333VfofSUmvTUSk4qbsWXr9+oo2Lm+B6wonLjzcQz+diEASer1GPzglbavcHzEcV5u+zIBfgE3P4DNCrFvwxe9IOU8lK8Lg/+A5k9Kf9cSStoOuJBe67mer47KV3+dxqPtDkqaNJOVAH/VLSVfbV5uO7BgwQJeeOEFPpu/gIvnz1GrYpBH51NUp06d4t577yU0NJR3332Xxo0bYzab+e233xg2bBgHDx4s0nGDgoIICrq118BkMqHT6Yq8f4UKFW5pfCFE0SmKwturDzF3wzEArmm/J1H7BSNajuC9mvfi9/WjkHYZdEHQcxbc9pB3JyyEECWEIyZdsGABZ8+eJTIy0ttTKpATJ05w1113SUwqSqzstTkaFViUvKthRf6OXj3KhPUTWPLPz1Qxfoka6NYoiBk9j1EpuFLBDpJ8AZYOzlpvoOnj0ONd0AW6bd7C+6Ty1YWcla9m9ydBHRWbBj+NMwknPV8Lx2pTnAlr9XX9bhRFIc1kuelPhtmG0WwlxXjz7Qrzc30vnrxkbzuQkpLCt99+y/PPP0/HLvfw8/df50oG//LLL9xxxx0YDAbKly9P3759AejYsSMnT55k1KhRqLK1Lbj+EimAWbNmER0d7by9Y8cOunbtSvny5SlTpgwdOnRg9+7dhXr9X3rpJVQqFdu3b+fBBx+kTp06NGzYkNGjR7N161bndjNnzqRx48YEBgYSFRXF0KFDSUlJueFx85o/wKRJk6hQoQIhISEMGTIEk8nkfKxjx44MHz6ckSNHUr58ebp165bv2LGxsTz99NNcu3bN+fpNnDgRyF29cerUKXr37k1QUBAhISE8/PDDXLhwIdecv/rqK6KjoylTpgyPPPIIycnJhXpNhSjtrDaFV5f940y8JmgXYgtaxo/9vuUDv7L4fd3fnngNbwzPbpDEqxCiWCtIPOqun4LEpNllj0nvu+8+Fi1alGub4hqTDhs2TGLS6+YsMWnJ4vj/nL1VXWH/j5d255LPMXTlUOrPrs83+74h0NoRNXqiy+tY/MiUgidej8fa2wzEb7CvN9BnLvSZI4nXUkAqX11I78HL/x2VrwG6bG0HJPlaKNkXLbu+8jXdbKXBhN88PCPYP7kbAbob/7e0KUqOytevvvuOevXqUbduXXr3e4S3Xh/H5Jg3nNuvXLmSvn378tprr/Hll19iMplYtWoVAEuXLqVJkyY8++yzDB48uFDzTE5OZsCAAXz00UcoisKMGTPo0aMHR44cITg4//40V69eZd26dbz11lsEBub+Q5P9sim1Ws2HH35I9erVOX78OEOHDuXll19mzpw5BZ7vunXrMBgMxMbGcuLECZ5++mnKlSvHlClTnNt88cUXPP/882zevLlAY7dp04ZZs2YxYcIEDh06BJBndYPNZnMGuRs2bMBisTBs2DD69+9PbGysc7tjx46xfPlyVqxYQUJCAg8//DDTp0/PMUchxI2ZLDZGLtnDqn3nUbBx1W82tatcZGn3VUSvnQynMz9AtxgE3aaCn8G7ExZCiHx4Kx6F/GPS632XLSZ94oknGDlyJOPHj3cmeoprTJqQkMBvv/3GlClTJCbNJDFpyeOozVGpsj73Ss/Xgkk0JvLu5neZtW0WaeY0ALrV7I7x/AucuGxhQOtaBVs/xmqxt7za+C6gQMWG8NAiqFDHrfMXxYckX13I0XbAalOwWG1oNe4rLDY62g5Iz9ciSzdlJl9VRVtwyxss1qwFwrRqFQsWLOCJJ54AoOPdXXnlxefZtHEDvbp3BWDKlCk88sgjTJo0yXmMJk2aABAWFoZGoyE4OJiIiIhCzaNz5845bn/66aeEhoayYcMGevbsme/+R48eRVEU6tatm++2I0eOdP47Ojqat956iyFDhhQq0NXpdHz++ecEBATQsGFDJk+ezNixY3nzzTdRq+3/f2rXrs0777xT4LF1Oh1lypRBpVLd9PVbt24d//zzD/Hx8URFRQHw5Zdf0rBhQ3bs2MEdd9wB2APiRYsWOT8oPPnkk6xbt04CXSEKIM1k4X+L/mLr8SQUzFzWvcdTdzbmg5rD0C15HNITQB8CvT6ARg94e7pCCFHiZI9Ju3fvzrVr19iwYQMdO3YEim9Mevz4cRRFoV69/Pt+S0wqMamvchS5qlUqVEjla0Gkm9P5ePvHTPtzGgnGBABaVWnFtLunEaZtyv0fb0anVdO3WeX8D5Z0Dn4cBCczv1BpPgDufRv8/N34DERxI8lXF9L7ZSVbMyzuTb6mZy64ZfDTZFXcSuVroTiSr4bMpHl2/n4a9k/udtP9r6WZOZ2QRoBOS40KrrlMwN8v91yyy95y4PDhw2zfvp1ly5YBoNf5cU+vvnz1xUJn8jUuLq7QFQQFceHCBV5//XViY2O5ePEiVquVtLQ0Tp06VaD9C/PHfu3atUybNo2DBw+SlJSExWLBaDSSlpZGQEA+jcwzNWnSJMe2rVu3JiUlhdOnT1OtWjUAbr/9dreMfeDAAaKiopxBLkCDBg0IDQ3lwIEDzkA3Ojo6R4VGpUqVuHjxYoHGEKI0u5Zm5sF5azl6wYYNIykBM1nQ+3keOX8AvrUnAqjUFB5aCGE1vDpXIYQojILEo+4cu6AOHTqUIybVarX079+fBQsWOJOvEpPaSUwqvMHxe65SQeayJbLc1g1YbBYW7lnIpA2T+C/5PwAaVGjA1M5Tub/u/ahUKl5d9g8A9zaKIDQgn57MR9bCsmch7Yp9vYFeH0Djfu5+GqIYkuSrC+k0OZOvgXr3jeXo+Zp9wS1JvhZOmtnRNzd3klylUuV7qZXVpmDIrDwuzGVZtyJ7y4F5CxZgsVhyLGagKAp6vZ5r165RpkwZ/P0L/22aWq3OFYiazeYctwcMGMCVK1f44IMPqFatGnq9ntatW+foWXUztWvXRqVSOS+NupETJ07Qs2dPnn/+eaZMmUJYWBh//vkngwYNwmQyFTjYLIjrLzXz5NgAfn5+OW6rVCpsNvk/LcTNXEhK596PVnA1OQArKQRHfMX6+9+i5rq34L+d9o1aDoGuk0Hrxj/KQgjhBgWJR4uDBTeJST/++ONiHZPWrFkTlUqV76JaEpNKTOrLHGdPRVbPV2k7kJOiKPyw/wdeX/86h68cBqBqmapM7jiZJ257Ao3a/oVUaoaFn+POAvDIHVVvfECrGdZPgT/ft9+OaAwPfQHlarr1eYjiSxbcciG1WoWfxv5m5u5EqDGvnq/SdqBQ0hyVr4X4Zj87TebXhlYP/uVyJF9Vio0vv/ySGTNmEBcXR1xcHL9t3Mp3v20iPKIS33zzDQC33XYb69atu+HxdDodVqs1x30VKlTg/PnzOYLduLi4HNts3ryZESNG0KNHDxo2bIher+fy5csFfh5hYWF07tyZOXPmkJqamuvxxMREAHbt2oXNZmPGjBm0atWKOnXqcPbs2QKP47B3717S09Odt7du3UpQUFCOb/6vV5Cx83r9rle/fn1Onz7N6dOnnfft37+fxMREGjRoUOjnIoSw2336NO3eW5qZeE2g9W1b2dPlaWp+N8CeeDWUgf7/Z7+sSxKvQgjhFhaLJVdMGhcXx969e4mMjCz2MWnZsmW55557mD17tsSkosTKWnArq+ertB3Isvb4Wu747A4e/uFhDl85TPmA8szqNovDww8zoOkAZ+IVYOXf50jJsBBdLoBWNcLyPuC1M7DovqzE6x3PwKC1kngt5ST56mKOvq8Zlpv/8btVjsWiDH6y4FZRZbUdKNp/A43KG8lX+1ixa34lISGBQYMG0ahRIxo1akSDhg2pXa8BPXr1YcGCBQDExMTwzTffEBMTw4EDB/jnn394++23nceLjo5m48aN/Pfff85AtWPHjly6dIl33nmHY8eOMXv2bH799dcc86hduzZfffUVBw4cYNu2bTz++OOFrmh47733sFqt3Hnnnfz4448cOXKEAwcO8OGHH9K6dWsAatWqhdls5qOPPuL48eN89dVXzJ07t9Cvm8lkYtCgQezfv59Vq1YRExPD8OHDnb218lKQsaOjo0lJSWHdunVcvnyZtLS0XMfp0qULjRs35vHHH2f37t1s376dp556ig4dOtCiRYtCPxchBHy4cT1952zFbArFqrrImHtNfFdWj/6H/4HxGlS+HZ7bBPV7eXuqxcbGjRvp1asXkZGRqFQqli9f7nzMbDYzbtw450rakZGRPPXUU7k+3F+9epXHH3+ckJAQQkNDGTRoUK6Vvv/++2/uuusuDAYDUVFRufoWAnz//ffUq1cPg8FA48aNnYvuCCF8j2NRpuwxqePnwQcf9ImY9OOPP5aYVGLSEs2RZ1WpHB1fs+4rzXb8t4MuX3ah61dd2XVuF0G6IGI6xHB8xHFebPUi+jy+vF+yw97SpP8dVfNeN+bQapjbDk5vs6838NAXcN8MWehVSPLV1Rz9VzPcnAh19Hz199Og0zgSvpJ8LQxH8lXvV7TLuRyVrzZF8dg3h47K12//70u6dOlCmTJlsuaT+ebfvVdvdu7cyd9//03Hjh35/vvv+fnnn2natCmdO3dm+/btzn0mT57MiRMnqFmzJhUqVADs34rPmTOH2bNn06RJE7Zv386YMWNyzGPBggUkJCTQvHlznnzySUaMGEHFihUL9Vyio6PZuXMnnTp14qWXXqJRo0Z07dqVdevW8cknnwD2vlgzZ87k7bffplGjRixevJhp06YV+nW7++67qV27Nu3bt6d///7cf//9TJw48ab7FGTsNm3aMGTIEPr370+FChXyTDKoVCp++uknypYtS/v27enSpQs1atTg22+/LfTzEKK0M1utPDB/ITNXpaFSAlDr4vnxkQhePPgFbLO/b9B6ODy9GspW8+5ki5nU1FSaNGnC7Nmzcz2WlpbG7t27eeONN9i9ezdLly7l0KFD3H///Tm2e/zxx/n3339Zs2YNK1asYOPGjTz77LPOx5OSkrjnnnuoVq0au3bt4t1332XixIl8+umnzm22bNnCo48+yqBBg9izZw99+vShT58+7Nu3z31PXgjhNgsWLMgVkzo8+OCDPhGT1qhRg927d0tMKkosW46er5mfYUtx19eDlw/S77t+3Dn/TtbFr0On0TGy5UiOjzjOxI4TCdYH57nf4QvJ7D6ViFat4sHbr1toy2KC316Db/rbF3qNbAbPbYSGfdz/hIRPUCmlrN78zJkzREVFER8fT3R0tMuP32baOs5eM/LL8HY0rpI7CHGVab8eYN6G4zzTrjrlgvS8vfog/W6vwnsPNXHbmMWF2Wxm1apV9OjRI1dPosL4ee9ZRnyzh/vql2P4nWWoXr06BkPBv5GyKQr7/rsGQINKIW5dYM3h6MVk0kxWqpULpIx/zud+OSWDs4nphPr7UbWcaxYAcxebzUZSUhIhISE3/aZfFE9y/jzPaDQSHx9f6PepG3HV+6gnHbt8nt5zl5GSYu+vFRl+mN87RhC0+mXISAL/stDnE6h77y2PdfXqVeasP0pgSGi+26YmJTK0Uy3Cwm5w6ZmbnDhxgurVq3P69GmqVKlSqH1VKhXLli2jT58+N9xmx44d3HnnnZw8eZKqVaty4MABGjRowI4dO5wVUqtXr6ZHjx6cOXOGyMhIPvnkE1577TXOnz+PTmdfgOKVV15h+fLlzn6K/fv3JzU1lRUrVjjHatWqFU2bNi1SFZkvc3dMKtzL1e+jrn6fF/mTeMb3yTksmIRUE6cT0gg2+KFWwbV0M5Gh/pQPKnxbJl+OSU9fO82kDZNYGLcQm2JDhYqnmjzFxI4TiQ6Nznf/yb/s5/PN8XRrGM68J7NViyechB/+l229geeh6ySvtr3yVCx7K/FoaSPvUC6mc1a+urftgNGUR89XqXwtlPTMRcsMuqL1fFWrVFnfHHroOwxTZtsBnSb3JQ5qaZ4uhCihFu/6k84zfyclpSo2jPS74yKba58h6Kch9sRrVCsY8qdLEq++Jjk5maSkJOdPRkaGS4577do1VCoVoaGhAPz111+EhobmuDS1S5cuqNVqtm3b5tymffv2zsQrQLdu3Th06BAJCQnObbp06ZJjrG7duvHXX3+5ZN5CCCGEyMlZ+UrWZ8aSWoMXfzmVmb8f4ujFZOd9V9KuMOb3MdT+qDYL9izAptjoXbc3fz//N4v6LCpQ4tVotrJ0zxkAHrkz20JbB1bAvLuyrTewGO6dLusNiFyK//KZPsbR89XdiVBnz1dJvhZZ1oJbRf8OQq1WYbMqHun7alMULJltB/Kqss3sgoC1hP4hFUKUPoqi8My3n7M2rhwqyoHmEp/3DKXL3gVw/h/7Ru1GQafXQOMbFbyudv0iKTExMflewpofo9HIuHHjePTRRwkJCQHg/PnzuS7l1Wq1hIWFcf78eec21atXz7FNeHi487GyZcty/vx5533Zt3EcQwghhBCu5fh0mHPBLa9Nxy0SUk18sO4I/7f1JBabwve7zvDdkOZ8+c8c3tnyDkkZSQC0r9ae6XdPp3VU60Id/7d/z5OYZiayjIH2tSuAJQPWTIBtmVftVG4BDy2E0Ko3P5AotST56mJ6P8/0fHUkDu09X+3voCarJF8Lw/EaOhLmRaFRqbAAnnjpHYlXlUqFVp1H5aujB62UvgohSoALyVfpMXcRV67URQWEhp5mXUcD5f4YBqYUCCgHfT+F2l3yPVZJtn//fipXzuo7ptffWqWF2Wzm4YcfRlEUZ69DIYQQQvguxdnzVeVcJKqkfGTMsFj5YssJPvrjKMlG+5WtAToN564ZaTNzHmc0b4BKoUl4E6bdPY3utbrnvVBWPr7dcRqAh1pEoUmMh++fhnNx9gfbvAB3x5TaQgBRMJJ8dTG9p9oOmLMlX6XytUiyXsOiV746Ft3yRLWpObPlgJ9GlecfDE0J+0MqhCi9Vh3cxtDFu8FcFwUrXepf5rPQ/ahXf2HfoFpbeHA+hER6d6LFQHBwsLM69VY5Eq8nT57kjz/+yHHciIgILl68mGN7i8XC1atXiYiIcG5z4cKFHNs4bue3jeNxIYQQQriW4/OhSmVvPQCg+PiCW4qisOLvc7y9+iBnEtIBqBcRTOv65/hi30fYLo1CY25MtOE5pt7fnv6N+qNWFe1z/8krqWw5dgWVCp4qswfmjclcbyAM+s6FOt1c+dRECSU9X10sq+erZ9oO+Os06DSeaXVQ0jgrX/2K/h2EM/nqgYynObPy1e8GC3s5+vdI2wEhhK9SFIUxvyxgyKJ4MFcFVQozu6SxIPUz1Hu+AFTQ/mV46mdJvLqYI/F65MgR1q5dS7ly5XI83rp1axITE9m1a5fzvj/++AObzUbLli2d22zcuBGz2ezcZs2aNdStW5eyZcs6t1m3bl2OY69Zs4bWrQt3+Z8QQgghCsZR+Wpfs8RxnxcndIt2nbzKA59s4YVv9nAmIZ2KwXqeaAdn9SOYuPUR4lM2Yw3+GgBVSk+q+XctcuIV7FWvekzML/cN5VY9m3O9AUm8igKSylcXc1zC7vbka7a2A44qyAxpO1AoWa0b1FDEb/4cf7w8cal/vslXtefmIoQQrpaYfo2en33E6bNNUKMmIOASazsYifxzEpjTILAiPPAp1Ozk7an6pJSUFI4ePeq8HR8fT1xcHGFhYVSqVIl+/fqxe/duVqxYgdVqdfZgDQsLQ6fTUb9+fbp3787gwYOZO3cuZrOZ4cOH88gjjxAZaU+EP/bYY0yaNIlBgwYxbtw49u3bxwcffMD777/vHPfFF1+kQ4cOzJgxg/vuu48lS5awc+dOPv30U8++IEIIIUQpkaPy1cMLRrvSySupvL36IKv+sccoAToN9zbxY1viVKbs+gOAMvoyjGs7jhEtRzD552N8u/M0I5bsYeWIuwgPMRR6TLPVxrad21mme48GKSftd7YbnbnegKTTRMFJ5auL6T1U+epMHMqCW0WWbrL3hDH43ULPVy+1HciLOtsf0pK6eqUQomTafGIPzd6ex5mzzVCh5vaqF/m70VYi14+zJ16rt7dXF0jitch27txJs2bNaNasGQCjR4+mWbNmTJgwgf/++4//Z+88w6MouzB8b09PCCWF3ps0adIUBaUoggKKoAIi2LBhA0FAQLEiYgGxF/BTAREREQRpgvQmvbcUShJSt8/3Y7ObRNKzJeXc18Wluzs7c2ZnM/vOM8/7nGXLlnH+/Hlat25NVFSU69/mzZtd61iwYAFNmjShR48e9O3bl65du+YQTUNDQ1m1ahWnTp2ibdu2PPfcc0yePJkxY8a4luncuTMLFy5k/vz5tGrVikWLFrF06VKuu+46730YgiAIglCBcF4aqlWqMtlwKyndzPTlB+k5az0r9sehVsFt1wVSu8FXzPq3J3+fX4uf1o8XO7/IyadPMqHbBAL1gbzavzlNIoO5nGrmye93u3qoFIVDqz7na8sLNFOfQQmoAvcvhp5TRHgtARs2bKBfv35ER0ejUqlYunSp6zWLxcJLL71EixYtCAwMJDo6mgcffJCYmJgc60hISGDYsGGEhIQQFhbGqFGjSE1NzbHMvn376NatG35+ftSsWZO33nrLG7uXJ/KNcTMu8dXivcxXpyhn9nDObHkjq+GWGzJfveA2dYrr+jycr5psObB2BfLQaAVBEEoNiqIwfc3XzF9jRas0R8HCpI5XGX1hLuw7Aio1dJ8A3Z4DdfFvlAnQvXv3fG/MFeamXXh4OAsXLsx3mZYtW7Jx48Z8lxk8eDCDBw8ucHuCIAiCIJQcV8MtQJ2Z+lpWxNdFO88zfflBrmY4Io3a1w3EFrSIz45/jIKCRqXhoTYPMfmmydQIqZHjvX46DR8Pu547P/ybbacSeHf1UV7q3aRwGzanw8qXaLnrG1DBmeDrqT16IYREuXsXKxxpaWm0atWKhx56iLvvvjvHa+np6ezatYtXXnmFVq1akZiYyNNPP82dd97Jjh07XMsNGzaM2NhYVq9ejcViYeTIkYwZM8Y1Tk1OTua2226jZ8+ezJs3j/379/PQQw8RFhaWwxTgTUR8dTO+yHxVWRzbMkvsQJFwfoYlcr463abeiB2w5x874AxQV3C4XzWI+ioIQuklxZTCgC/e4/iZlmjRodNdZUWXizTc8QZYMyAo0tFUq243X5cqCIIgCIJQZnGqBKrsztcy0HDrYrKRlxbvw2ZXaFDNnyoRG1ly8jUscQ4hdnCzwUy/eTqNqzTOcx31qgbx5sCWPLFwF3PXnaBd7Ur0aBqR/4YvHYGfRsDFg9gVFR/Y7uLOB94HNzU4rej06dOHPn365PpaaGgoq1evzvHchx9+SIcOHTh79iy1atXi0KFDrFy5ku3bt9OuXTsAPvjgA/r27cs777xDdHQ0CxYswGw288UXX6DX62nevDl79uxh1qxZPhNfJXbAzTgzXz0dAZA989UgsQPFIiNH5mvxUHszdsCaf+yASqVy1VNSMXjq1KlERERcMw2grLBu3TpUKhVJSUkAfPXVV4SFhblenzp1Kq1bt/ZqTd27d+eZZ57x6jYFobSy9ew+Wr3xISfOtEWFjmbVLvLvdX/S8J8pDuG1/i2OmAERXgVBECo0MiZ1PzImrXhkNdzKnvnqy4oKx8HYZGx2hZCADP7J6M8Px6disVu4td6tbB+9nR8H/5iv8Ork9pZRjOhcB4BxP+7lfGJ63gvvWQjzu8PFg6TpKnO/ZQKba46hbjURXvMjJSWF5ORk1z+TyeS2dV+9ehWVSuU6d27ZsoWwsDCX8ArQs2dP1Go1W7dudS1z4403otfrXcv06tWLI0eOkJiY6LbaioKIr27GW5mv2Z2vTretM35AKByu2AFd8Q3g3oodsCsK1v84X0eMGJF591KFXq+nQYMGzHvvLaxWa4nE4EOHDvHqq6/yySefEBsbm+ddqaJQlIFlcnIyEydOpEmTJvj5+REZGUnPnj1ZsmRJsbNs7733Xo4ePVqs9xaV/w6ynSxZsoTp06d7pQZBKM28tmYBg+buxJ7REgUrz7eJ5TfdhxgOLQaVBnpMgWGLIaiqr0sVBEEQCkFuY9Jp06ZhtVpLtF4Zk5YMGZMKThRXwy2Vq2F0ae8RYrQa+XTrbwDEmraTZk2lfXR7/nzgT1Y9sIp20e0KWENOXu7blFY1w7iaYeGJhbuvNa6Z0+Dnx2DpY2BJR6l7E0PUb7PZfh33dajlrt0qtzRr1ozQ0FDXv5kzZ7plvUajkZdeeon77ruPkEzncVxcHNWqVcuxnFarJTw83NUwNi4ujoiInA5n52PnMt5GYgfcjEHnFF89l79qsdldQqu/ToPJGTsgztcikSVgq8FcvHU4Ywc8Lb46w8FVKpVL8AXo3bs3X375JSaTiRUrVvDEE0+g1mh47dXJRd6GzWZDpVJx4sQJAPr37++6M+otkpKS6Nq1K1evXmXGjBm0b98erVbL+vXrefHFF7nllltyuAUKi7+/P/7+/iWqzWw257hzVlTCw8NLtH1BKOukmdMY8Pkcjp5phgYtOl0Sv91wgUa73gGbCUKqw8DPoXYnX5cqCIIgFJHcxqQ6nY4JEyYUeV0yJs0fGZMKRcWew/nqeK60aq9Wu5Vv9n7D1HVTSb88iCB6EBqYxid3LeauJncV+1yg16r5aGgbbp+zib3nknh9xSGm3tnc8WL8QfhpOFw+mtlv4GU2RjzA/q92EuKnpfd1kW7cw/LJwYMHqV69uuuxwWAo8TotFgv33HMPiqIwd+7cEq/P14jz1c3oNY7YAU86X43Zmnlld76K+Fo0MlwNt3LJfFUUx92vAv5prOmoLOkohVi2UP/y+BV0iu06jSrHD47BYCAyMpLatWvz2GOP0fnG7qxbvRK7XcFkMvH8889TvXp1AgMD6dixI+vWrXO91zntadmyZTRr1gyDwcBDDz1Ev379AFCr1Tm29dlnn9G0aVP8/Pxo0qQJH3/8cY4az58/z3333Ud4eDiBgYG0a9eOrVu38tVXX/Hqq6+yd+9elyviq6++ynU/X375ZU6fPs3WrVsZPnw4zZo1o1GjRowePZo9e/YQFBQEwLfffku7du0IDg4mMjKSoUOHcvHixTyP9X+neDn55JNPqFmzJgEBAdxzzz1cvXrV9dqIESMYMGAAr732GtHR0TRu3LjAbZ8+fZqbb3Z0Y69UqRIqlYoRI0YA107xSkxM5MEHH6RSpUoEBATQp08fjh07dk3Nf/zxB02bNiUoKIjevXsTGxub534KQmll+7mDtJw5l2NnWqJCS/OIGA40/4NG219zCK8NezliBkR4FQRByKKQ41GP/CuiMvPfMWnPnj1ZtmwZQKkdk2o0mjybCMqYVMak5YnszldVZl8QeynLfFUUhSWHltBibgtGLRvFueRzBKoaAvDBnS9zd9O7S3wTpkalAGbd0wqArzaf5re9MbDza/j0ZofwGhwFw3+Fm17gfzsvAHD39TVK1COmohAcHExISIjrX0nFV6fweubMGVavXu1yvQJERkZec561Wq0kJCQQGRnpWiY+Pj7HMs7HzmW8jThf3YzT+epJIdTp2FSrQK9RZ4mvNjuKonj9znBZJd3smArlp1NzjU/Zkg6vRxe4jkCghTuLejkG9IHXPG2x5d9sy4m/vz8JCQnYFYWxY8dy8OBB/ve//xEdHc3PP/9M79692b9/Pw0bOn7I0tPTefPNN/nss8+oXLkyUVFRdO/enZEjR+YYUC1YsIDJkyfz4Ycf0qZNG3bv3s3o0aMJDAxk+PDhpKamctNNN1G9enWWLVtGZGQku3btwm63c++99/Lvv/+ycuVK/vzzT8BxcrZYLDlqt9vt/O9//2PYsGFER1/72TsHueA4GU+fPp3GjRtz8eJFxo0bx4gRI1ixYkUhP2g4fvw4P/74I7/++ivJycmMGjWKxx9/nAULFriWWbNmDSEhITlCv/Pbds2aNVm8eDEDBw7kyJEjhISE5OluGDFiBMeOHWPZsmWEhITw0ksv0bdvXw4ePIhOp3Mdn3feeYdvv/0WtVrN/fffz/PPP5+jRkEo7cxc8wMf/2lEozRFwcL4NrE8GvcJqsOnQK2FnlPhhidALfeDBUEQclDI8ahHyGNMWlj8/f25cuUKQKkdk9rt9lyvm2RMKmPS8oZTaFVROp2v+1P289rXr7E9ZjsA4f7hjO/8Mp+urIMZO82iQt22rR5NI3j0pvp8u/5flCWjQbXJ8UKDnnDXJxBYhcupJlYfdAh197av6bZtC4XDKbweO3aMv/76i8qVK+d4vVOnTiQlJbFz507atm0LwNq1a7Hb7XTs2NG1zMSJE7FYLK7z2OrVq2ncuDGVKlXy7g5lIuKrm/FG5mv2ZlsqlSqHIGe22XN3cgrX4BSx/XQa0nxcS0GYM8VXfR7iq6IorFmzhg1/reG+EaM5c/YMX375JWfPnnUNGp9//nlWrlzJl19+yeuvvw44Tmwff/wxrVq1cq3LeTc++x2hKVOm8O6773L33XcDULduXQ4ePMgnn3zC8OHDWbhwIZcuXWL79u2uqUwNGjRwvT8oKAitVutap91uv0Z8vXz5MomJiTRp0qTAz+Ohhx5y/X+9evWYM2cO7du3JzU1NceAOD+MRiPffPONa3rEBx98wO233867777rqjMwMJDPPvssx9Sugrbt3P9q1arlOR3NOcD9+++/6dy5M+C4mKhZsyZLly5l8ODBgOP4zJs3j/r16wOOi5dp06YVav8EwdekmzMY8PlHHDnTCA1B6PRX+L3DORrsng02M4TWgkFfQM32vi5VEARBcBPOMekff/zBk08+ydmzZ0vtmNRut5OcnHzNPsiYVMak5Q2n0Jq94VZpEF93xuxkwp8TWH3KcVMhQBfAuBvG8Xzn57mcouGj5evx12moWSnArdt9vqWJB3dMJtp2ARtq7De/gq7bMy4jwJJd57HYFFrVDKNpVMVqtGW326/JiS5o+aKSmprK8ePHXY9PnTrFnj17CA8PJyoqikGDBrFr1y6WL1+OzWZzZbSGh4ej1+tp2rQpvXv3ZvTo0cybNw+LxcLYsWMZMmSI63dm6NChvPrqq4waNYqXXnqJf//9l/fff5/33nuvyPW6CxFf3YxT+DRZPJf5mpVVqs3cZjbx1Sria2HIkZurzUV81QU47vgXgM1u52BsCgDNo0JQq0voOtbl/sOSPXYgO8uXLycoKAiLxYLdbqf/wHt4dNx4Duzdjs1mo1GjRjmWN5lMOe4c6fV6WrZsmW9JaWlpnDhxglGjRjF69GjX81arldBQx13IPXv20KZNmxJlSBUl9H3nzp1MnTqVvXv3kpiY6Drpnz17lmbNmhVqHbVq1cqRS9OpUyfsdjtHjhxxDXRbtGhxTaaWO7Z96NAhtFqt684cQOXKlWncuDGHDh1yPRcQEOAa5AJERUXlO5VNEEoL288dZugXK7FkNEUFtIg4y5KIDeh2ZDqBmtwB/T8Ef9/ceRYEQSgTFHI86rFtF4H/jkmHDh3K1KlTWbdunYxJC0DGpIKncX6nHRFwOZ/zBUevHOWVv17hxwM/AqBVaRlz/Rgmd59MRJCjKdLfxxyO90YRQSW/xnaiKLDjc7QrXybaZiKOyjxhGkuDSz15M1N4VRSF/20/B8B9FdD1mpSUxKzlu/ELDC5wWWNaCgNbFP1cu2PHDlcsCsC4ceMAGD58OFOnTnVF1vy3OeJff/1F9+7dAcdNorFjx9KjRw/UajUDBw5kzpw5rmVDQ0NZtWoVTzzxBG3btqVKlSpMnjyZMWPGFLledyHiq5vxqvNV79hWdjek5L4WjnRzljjujIrIgUpVqKlWakUBnQ0FsOkCUBcQC1BcLNbcYwduvvlm5s6di16vJzo6mrgUMwlpZlJSU9BoNOzcuRONJqcYn/0uvL+/f4ExFampqQB8+umnOQZmgGvdJW0cAFC1alXCwsI4fPhwvsulpaXRq1cvevXqxYIFC6hatSpnz56lV69emM3F7JyWB4GBOb8D3tw24Joi4USlUpX6zqSC8NbaJXy4Oh210hAFMy+3ucCY2E9QHT0Lah3cNgM6PpI1700QBEHInUKOR0sD/x2TarWOy8zU1FQZk7oBGZMKJcGezfmKM/PVB4fvQvIFpq2fxue7P8em2FCh4r7r7uNG24081OuhHN+zw3EOg1PjyIJFwEJhvArLnoKDSx2PG/XmTKsZ7PruKDt3nKN93XAGta3B9tOJnLyURqBeQ79WPop98TF+gcEEhoR5bP3du3fP9/xRmHNLeHh4npndTlq2bMnGjRuLXJ+nEPHVzXij+VX22AEAtVqFVq3Caldc09OF/HE2LdOoVQXmqOaHSqVCrVZhsyvY7AqeyuLOK/M1MDAwx1Qqjdoxlb95y1bYbDYuXrxIt27dSrTtiIgIoqOjOXnyJMOGDct1mZYtW/LZZ5+RkJCQq9NAr9djs+XvBler1QwZMoRvv/2WKVOmXJOxlZqaip+fH4cPH+bKlSu88cYb1KzpuBu5Y8eOIu/X2bNniYmJcW3nn3/+Qa1Wu5oY5EZhtu10JeS3v02bNsVqtbJ161bXFK8rV65w5MiRQjsVBKG0YbSYGPDZPA6dqYuaSmj1l1jV7jT19nwAditUqgODvoTq1/u6VEEQBMHN/HdM6qRNmzYyJi0AGZMKniZnw63M57zYcCsxI5E3/36T97e+j9FqBOCORnfw2i2v0TS8aa4ZyUdd4qsbpv1f2AWLRkLi6cx+A69CpyfoqFLxbE+Ytfook5bu57rqIfxv21kA+rWKJtAgcpngPqS7hZvJcr56IXYgm9LnDdG3POF0vgZk5uaWBE3m+20evH2YV+zAf1Fn1lKnXgOGDRvGgw8+yJIlSzh16hTbtm1j5syZ/Pbbb0Xe/quvvsrMmTOZM2cOR48eZf/+/Xz55ZfMmjULgPvuu4/IyEgGDBjA33//zcmTJ1m8eDFbtmxx1FOnjivL5fLly5hMply389prr1GzZk06duzIN998w8GDBzl27BhffPEFbdq0ITU1lVq1aqHX6/nggw84efIky5YtY/r06UXeJz8/P4YPH87evXvZuHEjTz31FPfcc0++3Q8Ls+3atWujUqlYvnw5ly5dcrk0stOwYUP69+/P6NGj2bRpE3v37uX++++nevXq9O/fv8j7Igi+5nTSaa6f9QqHzzRAhYaWESc41Og36u16zyG8NusPj2wQ4VUQBKGC0ahRIxmTFoCMSQVPY3fFDni34Va6JZ03Nr1BvTn1ePPvNzFajXSp2YWNIzfy632/0jIi76iRI/GZ4mtECZyvigL/zIPPb3MIr6G14KE/oPNY1wcx9uYG3NioKkaLnce+28Vv+x1xB0M61Cr+dgUhF0R8dTOGTEHUo7EDrsxXEV+LS7rZCuT8DIuLM4PG7qFfMLuiYLXn7ny9phZV1jSSL7/8kgcffJDnnnuOxo0bM2DAALZv306tWkX/IXn44Yf57LPP+PLLL2nRogU33XQTX331FXXr1gUcd9ZXrVpFtWrV6Nu3Ly1atOCNN95wTQEbOHAgvXv35uabb6Zq1ap8//33uW4nPDycf/75h/vvv58ZM2bQpk0bunXrxvfff8/bb79NaGgoVatW5auvvuKnn36iWbNmvPHGG7zzzjtF3qcGDRpw991307dvX2677TZatmzJxx9/nO97CrPt6tWr8+qrrzJ+/HgiIiIYO3Zsruv68ssvadu2LXfccQedOnVCURRWrFhxzbQuQSjtLDuyjHYfDSYtsSsAL7Y4wjLlE3THV4HGALe/C4O/Bj/3daoVBEEQyg6ldUwaERHB4sWLc92OjEllTFqecF6lqlG5jEd2RfFYdITFZmHejnk0mNOACWsmkGRMokW1Fvx6369sHLmRrrW65vt+o8XG6SuOrizFjh3ISIQf7oeVL4Hd4ug38OgGqNEux2JqtYr37mlFZIgfpy6nYbLaaRIZTKsaMm4V3ItKqWBhLefPn6dmzZqcOnWKOnXquH39/5y8wpD5/9CgWhB/jrvJ7esH+GnHOV5YtI+bG1fly5EdAOjw2p9cTDGx/MmuXFe9fJ8oLBYLK1asoG/fvsUeFOw4ncCgeVuoUzmAlU924tSpU9StWxc/P78ir+vEpVTSTFZqhQcQFqAv+A1FxGy1cTguBbVKRfPokHydulfSTFxIzCDET0edKqU3I8zZXTYkJAS1Wu4BlTXk+Hkfo9FYovPUf3HHedRiszBhzQRmbf6IKNMc9Eok70SvYWDiN6DYILw+DP4KovJvoFIaSUhI4OO/jhcq7yotOYnHb25QouYuxeH06dPUrVuXc+fOUaNGDa9uW3APnh6TCp7FHefR7Lj7PC8UjIxnyj5yDAtGURT2X7gKQLOoEFDBwZhkAK6rHuoy7xSW/M5VdsXOjwd+ZNLaSZxIPAFA3bC6TL95OkOuG4JGfa3xKbdz6f7zV+n34SYqB+rZ+cqtRd5nzu+An0bC1bOg0Tv6DXQYk2+/gZ1nErj3k3+w2hWm9mvGiC51i77dUkRxx7JFfd/t9XRcf/31Mh4tBBJi4Wb03owdyM35KpmvhcIZO+DnhpBWT8cOmLNFDhQUkaBRedaFKwiCAHDu6jnuXXQvW85vIdzyBBFKEB8GzKJzwi7HAtcNgn6zweCmJgnFxG63k5SUVOjlw8LC5OJNEARBEIRyQ/bLwuyZr67X3ND/VFEU/jjxBxPWTGBP3B4AqgVW45UbX2FM2zHoNUUzKB2Oc4jDjYoaOaAosOVD+HNqVr+BwV9BdJsC39q2djjvD2nD3ycuc297iRwQ3I+Ir27G4MWGW365ZL5aJHagUDgF7AA3xA5oMmMHbB4SPK2Zgrq2EI3B1CK+CoLgYX4/9jsP/PwAVzKuUFndnVvsdZhjmECkPRG0ftDnLbj+wXzdBd4iKSmJWct34xdY8ODdmJbCuDvaeN3BKgiCIAiC4CmyXxeq/zM0U9ygvm45t4UJayaw/sx6AEIMIbzQ+QWeueEZgvRBxVrnUWfea1EiB9ITYOljcHSl43GzAXDnnCLFXt3eMorbW0YVoVJBKDwivroZg9Z7ma/ZhUO9RpyvRcEpYAfoS/4n4BRf7R5zvjqOqb4I4qt8DQRBcDdWu5XJf01m5qaZAFxftQsPXWrAo/oZaFQKVGnkcBdENPdtof/BLzC4UFOnBEEQBEEQyhvOK1RVtrxXFSoUFEpy+XrsyjFe2fgKvxz5BQCDxsDYDmMZ33U8VQKqlKjmw3FFFF/P/gOLRkHyeUe/gd4zod1DpcIIIAhORHx1M07nq8nihYZb2Zyv3nDcliecsQNuabjlYcHTki12oMBaMvVZcb4KguBOYlJiuG/xfWw4swGAF1uO5MEjJ2mu/AgqsLUYguaOd8FQPIeDIAiCIAiC4H6c14XZdUiVyjFDX6Ho14xmq5nL6Zd58LcHOZ12GrVKzcjWI5ly0xRqhtZ0S82Fdr7a7fD3bFg7o8z3GxDKPyK+uhmDNzJfzdeKrzqNiK9FId1sBXK6h4vbe87TsQPOKAldIZyvkvkqCOUTX/bG/PPknwxdPJRL6ZcI1gfzS8fnuGHr1/ibrpCuGEjs/jrVb37YZ/UJgiCUJypYL2RBEDyM85SSPXJArQK7kjMPtiAsNgtxqXFcTLpIqjkVO3YGNh3I9Jun07RqU7fVm5RuJj7ZBBSQ+Zp2GX5+BI7/6XjcYjDc8Z7P+w0IQl6I+OpmnLEDdsWR1VmYnM6i4sp8lYZbxSa7gO3sqpieno6/v3+R1+U8xJ6KHbDYCi++ql0RCI7Be0ENugRBKBukp6cDuKWjdmGx2W1M3zCdaeunoaDQuloL/qx1K+Eb3kOFwhF7DfbcMJt7by5GF1pBEAQhByUdjwqCIOSG4nK+Zl0XOv5fKdTNHpvdRnxaPHGpcdgVO1hAq9by070/0aFmB7fX64wcqFHJnyBDHnLV6U2w+GFIiXX0G+j7NrR5QGIGhFKNiK9uxqDLEshMVg+Jr87M11wabnkya7Y84Ypu0GvQaDSEhYVx8eJFAAICAookWtrMZhSrGbPJhtFY8hiD/2IymVDsduwWLUZV/o5qm11BsZpRgIwMo0uMLW3Y7XbMZjNGo1E6i5dB5Ph5D0VRSE9P5+LFi4SFhaHRuP8ckxvxqfEMWzKMNafWAPBc82G8mXIFzfbPAPiftTvLqz/D1727e6UeQRCE8k5Jx6NC0ZHxTNlHjmHBZJitjutDRY3RaARwPLbZyTAaUdlzl4Tsip2E9AQupV/CpthAAb1djz3DTvOazYmOjvZIvc7IgSa5RQ7YbbDxXVg3ExQ7VGmc2W+gmUdqEQR3IuKrm8neFMlktRNocP82jJZr80r1EjtQJNLNOZuWRUZGArgGvEXBaLFxOdWMTqPCluznviJxCC+xSY4fSW2aX4FiqqLAxaQMADRpfq5IhNKGoihkZGTg7+8vFxZlEDl+3icsLMx1nvI060+v577F9xGbGkuALoBf2j1Nzz0/QPplLGp/njeOZI2uO7/f27HUnmMEQRDKIiUZjwpFR8YzZR85hgVjsti4lHmtqkp1XKteTDZisSkoyXoMupw39hVFIc2SRpIxCZvdcc2s1WgJ8wtDp9MRVsWzY1Kn8/WayIGUeFgyGk6tdzxuNRRufwf0gR6rRRDciYivbkatVqHTqLDYFI/lvjqFQ79cnK8ivhaODJf46vgTUKlUREVFUa1aNSwWS5HWdTg2mam/7qJqkIH/PdLJrXXGJGYw9eet6DVqVjzdrVCDiifnbMRosfHtQx2JrlQ6p61ZLBY2bNjAjTfe6NVp1IJ7kOPnXXQ6nVccr3bFzhub3uCVv17BrthpUaUpa2v2oMrmjwDICG/GnfEPc8weydv9mlEzPMDjNQmCIFQkSjIeFYqOjGfKPnIMC2brqStM/Ws/jSKCmXu/I5t15jc7OHEplZl3t6BD3cqAQ3Rde2ot7/3zHscTjgNQLbAaT3R4goFNB6JVa70yJj0Sl0uzrZPrYPFoSLsIugC4/V1oPdSjdQiCuxHx1QMYtBosNqvHhFDXlPncxFfJfC0U6bl8huCY8lXUH5TQYBsXUmxcNZvx83Ov8/VSRhoXUmzUqWwodP5XskXFpRQbRkXj9nrchUajwWq14ufnJwOlMogcv/LH5fTLPPDzA6w8vhKAp5sO5t3kRDS7vgHAev1IBh3ryzGbhV7NIxjUtoYvyxUEQSjXFGc8KhQdGc+UfeQYFkyGTcOFFBuR4SrXtWGKVcWFFBtGu+N6cf3p9YxfM55/zv8DQCW/SkzoOoGxHcbir/OemUdRFI7GOWMHQhwxA+vfhPVvAQpUa+aIGaja2Gs1CYK7EPHVAxi0alJNnstf/a9r07lNEOdrYckwW4Gc0Q3FJdjPcRxSTVZsdsWt03BjrzoiB6JCC/+jF6jXcAlIy9xHQRCE/Pj77N8MWTyE88nn8dP68UvbJ7h172JUGQmgD4Y75zDzdBMOXDpFlSADr9/VQqb2CYIgCIIglAGc5iynXgBZkYVHr5zkvQUjXTff/bX+PHvDs7zQ5QXC/MK8XmvMVSMpJitatYq6hmT4egic2eR48foHofeboJeZV0LZRMRXD+A8sZksHna+6q89gYr4WjhcTcvcKL4CpBqthAa4765rlvhaeAdrYGZXyDSTiK+CIOSNoijM+mcWE/+aiE2x0Sy8IX/VvIVq/3zqWCCqFQz+ir8TQvh801YA3hrUgspBHggzFwRBEARBENyOKfO6N7v4alUc15jjV79CmnYtWrWW0deP5pUbXyEqOMondQIu1+s9YUfRf/okpF8GfRDcMRtaDvZZXYLgDkR89QDOCABPZb5m5JP5apHYgULhzM39b+xAcTBoNRi0akxWO8lGi5vFV0fzrKiw4oivnvn+CYJQ9knMSGTmqZls27sNgLGN+jM75SqaPd87FujwCNw2natmNc//tAGAoR1rcUuTCF+VLAiCIAiCIBQR52xcg1ZDbEos0zdMZ9O5KvjTERU67rvuPqbdPI0G4Q18XCkciUnkRe3/eDx9meOJiBaOmIEqvq9NEEqKuuBFPMtHH31EnTp18PPzo2PHjmzbti3f5WfPnk3jxo3x9/enZs2aPPvssxiNRi9VWzgMWoeg5+nM1+yxA1mCr4ivhSG36IaSEOLvEFyTje5tjhCT5PhuRxYxdgAkdkAQhNzZdmEbHb7owLbkbeg1en5vO5Y5Z3ahidkFhlC451vo+xZoDUxe9i+xV43UqRzAxL5NfV26IHiU8jgmFQRBECo2Tn3g0JX91J9Tn7k75mLHDMD4LpNYOHBhqRBeSb7Abdsf4nFtpvDa/mF4+E8RXoVyg0/F1x9++IFx48YxZcoUdu3aRatWrejVqxcXL17MdfmFCxcyfvx4pkyZwqFDh/j888/54YcfePnll71cef4YdJ4VQo25NdzKDOWXhluFw+V8dUPsAGRFDyRnuFfwjEt2OF+jJXZAEIQSoigKc7bOoesXXTlz9Qw1dNU40/g+eu/4BpXxKlRvC49ugGZ3ArBsbwy/7IlBo1bx3r2tXecWQSiPlNcxqSAIglBxSbeks/r4XwAcuLSbDGsGN9S4gVvr3QxA1QDfRQxkJ+LqHrSfdadexr8kK/7s6/Q+3P4u6Epn82hBKA4+FV9nzZrF6NGjGTlyJM2aNWPevHkEBATwxRdf5Lr85s2b6dKlC0OHDqVOnTrcdttt3HfffQU6E7yNwYOxAxabHYtNAf4jvkrDrSLhztgBgBA/h/M1xc3O11iX87UI4qtexFdBEHJy1XiVwT8N5umVT2OxW3ikbi/2aCKIPPCzY4FOY2HkSqhUB4C4q0Ym/bwfgCdubkCbWpV8VLkgeIfyOiYVBEEQKh5Wu5X5O+fT8IOGrDy+BoAw/2B+GfILmx/aTM1Qh+jqc+3AZkG9Zgo3nJyFKiOR/fZ63GF+nUrt7/FtXYLgAXxmYzGbzezcuZMJEya4nlOr1fTs2ZMtW7bk+p7OnTvz3XffsW3bNjp06MDJkydZsWIFDzzwQJ7bMZlMmEwm1+OUFEeIs8ViwWJxr1DmRKdxdIFOM7p/G9nFPY3K7lq/RuUQZI1mq8f2q7Tg3L+S7GeGxSFM6tWKWz6vIINDxE1MM7rt8zdZbFxJc0wJqRqoLfR6/XWO719Khue+4yXFHcdQ8B1y/MoWu+N2M/TnoZxIPIFOrWNJ8we5/fBKVOYUFL8wbP0+RGnUGxTAYiHNZOW5H/eSbLTSonoIj3arXWaPtcViQVFs2O0F3wxVFJtrbFDc93mTsnpMSiPleUwqeA75LSz7yDEs+8gxzIldsbPk8BKmrJ/CsYRjANTSVwYrDGtxD33qNcVqteL0H2X4UjtIOovm59FoYnYCcLnpcAbuvgWd3o9qRbj2FXLHW2Ngq1XljnIrBD4TXy9fvozNZiMiImfzjoiICA4fPpzre4YOHcrly5fp2rUriqJgtVp59NFH853iNXPmTF599dVrnt+wYQMHDx4s2U7kQdIVNaBmx+49aC/sduu6r5oBtKhR+POPlagyv+tH41SAhrMXYlix4rxbt1laWb16dbHepyiQbtIAKjZvXMcBfclrSUt0HPOtu/bhF7u35CsELhsBtOhUCpv/+tN1rAsi9qyjloNHT7DCeswttXiK4h5DoXQgx690oygKf1z5g88vfI5FsVBDW4VlAS1os+8nAK4ENmRLzcc4usvOuY2/cz5Vxdk0FRczQEGFTq3Qr2oCq/9Y6eM9KT4pKSmcuKDGLzC4wGWNaSmsNp4gODi42O/zJpcvX/bq9soz5XlMKnge+S0s+8gxLPtU9GOoKAp7U/fybcy3nMg4AUCIJoTBkYMxpfZgYzpcOHuGFStOAXA+83rx0NHjrDAd9Xq9kUk7aXP2U9S2dMyaAHbXGs3vqe0woyFKb2Xlyt+9XlN5w1tj4C0xMh4tLGUqwG3dunW8/vrrfPzxx3Ts2JHjx4/z9NNPM336dF555ZVc3zNhwgTGjRvnenzhwgWaNWvGjTfeSJ06dTxS54qreziYdJHGza6jb4eabl33mYR02LkJf4OW22/v5Xo+bed5Fp06SHiVavTte71bt1nasFgsrF69mltvvRWdTlfk95ssNpR/HNMv7uh9myuvtSRsthxg95UL1KjXiL431y/x+gC2nkqA3TuoHh7I7bd3LfT7zm88xR8XjlElugZ9+17nllrcTUmPoeBb5PiVflLNqTz+++P87/z/ABhd+xY+SEvDcMnhLlhdaQhTEvsQu0eHksv7I0IMTOzTmD7XRXqxaveTkJDAqY0nCQgOK3DZ9JQkbu1Wj/Dw8GK/z5ucPn3aq9sTclJWxqSC55DfwrKPHMOyjxxD2B6znUl/TeKvM45s1yB9EM92fJZnOjxDsCGYycsOQtx5mjVu6LpOPbT6GOtiT1GjVh369m3ivWKtJtRrp6E59QkA9ui22PrNJW7bYfy09eDYGTo2rkHfvs29V1M5xVtj4E61G5a82AqCz8TXKlWqoNFoiI+Pz/F8fHw8kZG5X+y98sorPPDAAzz88MMAtGjRgrS0NMaMGcPEiRNRq6+NsDUYDBgMBtfj5ORkAHQ6ncdO0P6ZmZtWO27fhsXusD/667Q51u1v0Hlsm6WV4h7DVHOW1BASYECrKXn0cViA4zuWbra77fO/lOaYahEV6l+kdYZk1pLhxlo8hSf/DgXPI8evdLI/fj+DfxrM0cvnCLX158WwujxzeiEGjFxRghlneZz1sa1cy0eG+HFd9VBaVA+lRY0QrqseSrXg8tHgQKfToVJpUKsLzvdWqTSu73Rx3+dN5G/PfZTnMangeeT4lX3kGJZ9KuIxPHz5MBPXTmTJoSUA6DV6Hm/3OC93e5mqgVVdy1kyY10DDFmfkb8+UztQvDieSDgFP42A2D2Ox53Gou4xBa2iAg5z4rKj0XTT6NAKdyw9gbfGwFptmfJz+hSffVJ6vZ62bduyZs0aBgwYAIDdbmfNmjWMHTs21/ekp6dfM5jVaBxfCkXJzbvjGwxaR00mDwRYZ1gyG0Xpc34O+szPweeh2WWA9MzPUK9Ru0V4BVzu2WQ3NtyKvepothUVVjQRJFDv+C6kmaXhliBUNL7c/SVPrHiCDIuVhtZ3mMpfDE1xNAzaam/CDMNzRNSrx1NRQRhjjjLizluIDg/ycdWC4FvK85hUEARBKF+cu3qOqeum8tXer7ArdtQqNQ+2epCpN02ldljta5Z3ahLOpuDgg2bdB5bCsifBlAz+lWDAPGjc2/FaZrbrkXhHDnrjCO/GOAmCt/CpTD1u3DiGDx9Ou3bt6NChA7NnzyYtLY2RI0cC8OCDD1K9enVmzpwJQL9+/Zg1axZt2rRxTfF65ZVX6Nevn2vAWxpwnsw8Ib4azQ7hMECX89C5tmkT8bUgMsxOAdt935kQf8fduRSj+wTP2KRM8TW0iOKrwfHdSDOJ+CoIFYU0cxpPrHiCr/d+DUB/v+eZmT6fpupzKKg40+wx6vWaxK+hgYBjmt6KFUeoGmzIb7WCUGEor2NSQRAEoXxwJf0Kr298nY+2f4TJ5mjeeGfjO3n9ltdpXi3vafpma6bxKBfx1RN6RQ4sRlg1EbZ/5nhc8wYY9DmE1sixmMkG5xIdztfGkSK+CuUTn4qv9957L5cuXWLy5MnExcXRunVrVq5c6Wp4cPbs2RyugkmTJqFSqZg0aRIXLlygatWq9OvXj9dee81Xu5ArBg/eSXI6X/3+Ixx6/e5VGcYpvga4UXz1qPM11L9I7wtyia8FdygUBKHsc+jSIQb/NJgDlw6gVqmZFzGSoTFfE6g2YTZURn/P59Spf7OvyxSEUk15HZMKgiAIZZtUcyqz/5nN25vfJtnkiKu5sfaNvNHjDTrV7FTg+7Ocr1nXvll6hQevF6+cgJ+GQ9x+x+Ouz8LNE0FzbaRAXIajKXaVID2Vg8QY4MRut5OUlFSk94SFheUafST4Hp8HNIwdOzbPKV3r1q3L8Vir1TJlyhSmTJnihcqKj0HnvJPk/pNZutO1qftv7IAXTqDlhPTM6fhudb76ecD5etVx9y+6iLEDTlE5VZyvglDu+W7fdzy6/FHSLGnUDYzgz/BO1Dv7E6jgTEg7ao9eAMFlu2mWIHiL8jgmFQRBEMomZpuZ+TvnM33DdC6mXQSgdWRrZvaYSa/6vVCpVIVaj8nig9iB/Yvg16fBnAoBleGu+dCwZ56Lx6Y79kVcrzlJSkpi1vLd+AUW7nMxpqUw7o42Xm8CKxQOn4uv5RGvZL7qcne+WmySM1YQzsxX9zpf3S++xmU6XyNDiud8TZfMV0Eot2RYMnh65dN8uutTAB6q3pm56Rnoz67FpqhYHHI/dz/5HkjDAkEQBEEQhDKDXbGzcP9CJv81mVNJpwCoX6k+M26ZwT3N70GtKpqr0WkIyy6+GjwVO2DJgN9fgl2OGCxqd4WBn0FIVL5vc4mvESHuracc4BcYTGBImK/LENyAiK8ewJWhYvFA5qtLOMx56DwZdVDecGW+6tyZ+ZoZO5DhntgBo8XGlTQzUHTna6DEDghCuebYlWMM/mkwe+P3olJU/Nz4bu48sQmVNYN4JYzJmmeZPvpRtCK8CoIgCIIglAkURWHFsRW8vPZl9sXvAyAyKJIpN01hVJtR6HKZrl8YXLEDutxiB9yoHVw6Aj+NgIsHARXc+ALc9BJoCpacYtId/20cKU1ghfKLiK8ewHUy80DzK2fsgF8ezldPbLO8kdVwy31f/+zOV0VRCj0NJC/ikx2uVz+dmlD/ov3QBmbul9lmx2y15whXFwShbPPjgR95eNnDpJhTqONfhc0RHYk6shqADbYWjLM+zpxRt1EtpGg3bQRBEARBEATfsOnsJiasmcCms5sACDWEMr7reJ7s8CSB+sASrTsr8zWX2AF3aQd7voffxoElHQKrwd3zoQj9BrJiB8T5KpRfRHz1AK7YAYv7nYdZwmFOQU2nEedrYXHFDrjT+eqXJXiarPZrxPGiEpPkEF+jQ/2LLOQGGLK2nW62otfqS1SLIAi+x2Q18fyq5/lw+4cAjIxqz/wME9pTG1FUGt6zDeYDyx0807MJnRtU8XG1giAIgiAIQkHsi9/HxLUTWX50OQB+Wj+e6vAUL3V9iXB/9+R2OvWB7IYcvcapV5RQOzCnwYoXYM8Cx+O6N8Hdn0JwRKFXcSXNTIrFcb3bKEKcr0L5RcRXD+CxDBWyYgfyynwV8bVgMjKzUN2Z+Rqo16JSObo0JhstJRZf45IdzbYiQ4vuXtNp1Oi1asxWO6kmK2EBIr56AqvNzsZjl+lUv3KJj7cg5MepxFPcs+gedsTsAAV+btCP/qf+QWUzYQ+OYpztaZYm1KJbwyqMvaWBr8sVBEEQBEEQ8uFU4ikmr5vMgn0LUFDQqDSMajOKyTdNpnpIdbduK7fMV7c4X+MPOmIGLh8BlRq6T4Buz4G6aNdFx+JTAahZyf+aaEVBKE/It9sDuDJfrR5wvlpynzKv12SdQN0x7b0844pucKP4qlarCDZoSTZaSc6wUq2EjRqdzteo0KI123ISZNCSYDW79lVwPz/tPM+EJfu5r0NNZt7d0tflCOWUpYeXMmLpCK6arlLbrxKbq3Ug+vh6AJSGtzGZJ1i6P42IEAPv3dsajVrO/YIgCIIgCKWR+NR4ZmyYwSc7P8Fid/QKuaf5PUy/eTqNKjfyyDazYgfclPmqKLD7W1jxIlgzICgSBn0OdboWq76jFx3ia2NxvQrlHBFfPYAnm1+l59EsKvs0ArPNnuPkKuTEGd3gztgBcOS+JhutpBhL3nQr7qpTfC1ebmOgQUNCGqSarCWuRcidAzFXAfhlTwyTbm/manQmCO7AbDMz/s/xvPfPewAMr9aaT40WdGe2gFoLPabwg/ZOvvv5ABq1ijlD2lAlyODjqgVBEARBEIT/ctV4lXe3vMusLbNIs6QBcFv923j9ltdpG93Wo9t2Rgvk5nwtslnMlALLx8H+Hx2P6/eAuz6BoKrFru9ofAoADUV8Fco5ohZ4AGcnQU/EDricr7qcma/ZT6Zmq4iv+eH8DN0ZOwAQ4q/jQlIGycaSC56xVx2xA1FhxRRfM53R6SZxvnqKC4mOY5RutrFifyyD29X0cUVCeeHs1bPcu+he/jn/DyiwpG5vBpzdgcpmhtCaMOhLDmoaM/njvwF47rZGdKxX2cdVC4IgCIIgCNkxWo18vP1jXt/4OlcyrgDQoXoHZvaYyS11b/H49hVFyYod0OUmvhZBr4jb74gZuHIcVBq4ZRJ0eQbUJWvufCTe6Xwt4dRRQSjliPjqATya+ep0beYROwCS+1oQLvewmzNlgjObbrnD+RpbYueroxZxvnqOC0kZrv//aed5EV8Ft/Db0d94cOmDJGQkUMsQypYqbYk+tdnxYuPbof+HpKiDeeLDvzFb7dzcuCqP3ljft0ULgiAIgiAILqx2K9/s/Yap66ZyLvkcAE2qNOG1W17jriZ3eS0i0GpXsCuO/y927ICiwI4vYOUEsJkgpDoM/BxqdypxfYqiuDJfpdmWUN4R8dUDeCPz9b95pWq1Cq1ahdWulCw4uwLgih1wt/PVTwdAcoY7nK8ly3x17luaiK8eQVEUl/MVYNupBM5cSaN25UAfViWUZax2K5PWTuLNv98EYHiV6/jUZEV3fgeodXDbdOj4KAow/vvdnLqcRnSoH7PuaY1acl4FQRAEQRB8jqIo/Hz4Zyauncjhy4cBqBFSg1e7v8qDrR5Eq/au/JJdXM2r4Va+/WKMyfDrU3DgZ8fjRr1hwFwICHdLfecTM0gz29CoFOpUDnDLOgWhtCLiqwfwReYrOE6iVrNNnK8FkG52CJK5fYYlIcRNzlejxUZCmhkovvM1KNP56txXwb0kZ1hJy/xbbF+nEttPJ7J41wXG3eqZoHyhfHMh+QJDFg9h09lNoMDiWrdw1/m9qOwWCKsNg7+E6o48sO+2nOa3fbFo1So+GHo9lQL1Pq5eEARBEARB+OvUX4xfM55tF7YBEO4fzsRuE3m8/eP4aYt3TVdSss/EzT5T1qBxXAcrClhsCnptLuJrzG74aSQknnL0G+g5FTqNBTe6do/EOfJeI/xBpylZfIEglHZEfPUATku/R2IHLPmLr+lmGxZxvuZLVuyA+zNfAZJLKL46m2356zSEZq6zqGTFDkjmqyc4n5QOQOVAPfffUNshvu48zzM9GooLUSgSq06sYtiSYVxOv0xtfQibK7ci+uwOx4tN74Q7PwD/MAD2n7/K9OWHABjfpwlta1fyUdWCIAiCIAgCwM6Ynby89mVWnVgFQIAugHE3jOP5zs8T6hfq09qcM3H1GnWOa5Ts+a9mmz1H824UBbbNh1WTwGaG0Fow6Auo2d7t9R3JbLYVFaC4fd2CUNoQ8dUDuDJfLR5suJWLcOi8m+UJ0bc8YfRQw62szNeSuU2z570WNw8oUGIHPIozcqB6JX96NY8k2E/LhaQM/jl5hc4Nqvi4OqEsYLPbeHX9q8zYMAMFheHhTfjUZEMXsxc0euj1OrR/2OUuuJph4fGFOzHb7NzaLIJRXev6eA8EQRAEQRAqLkevHOWVv17hxwM/AqBT6xjTdgyv3PgKEUERPq7OgVOPyB45ALn0izFkPshIhF/GwuHljsdN7oD+H4K/Z274O52vIr4KFQERXz2A806SRzJfC4gdAGm4VRAec766Ml9L5nyNveoQ9qLCij89xel8TZPYAY/gbLZVPcwfP52Gfq2iWbj1LIt2nhfxVSiQuNQ4hi4eyl+n/0KlwOLq3bgr5l9Uig3C68HgryCqlWt5i83Oi4v2ci4hg5rh/rwzqJXXGjUIgiAIgiAIWVxIvsC09dP4fPfn2BQbKlQMazmMV7u/Sr1K9XxdXg6cpqzsTlfI2S/GpVmc3wmLRkDS2cx+AzOg4yNujRn4L0czna/REvcqVAAkWMMDODNU7ApY3RwBkJGPcCjia+FIdzXccu+9B3c7XyNDitdsC7KJr+J89Qgu52uY4xgNalsDgBX/xpY481co3/x16i9az2vNX6f/orY2kPMRnbj7wl6H8HrdQMyj/uJfex3+t+0sE3/eT/8PN9F8yh/8cSAevUbNR0OvJzSgeHEkQsVmw4YN9OvXj+joaFQqFUuXLs3xuqIoTJ48maioKPz9/enZsyfHjh3LsUxCQgLDhg0jJCSEsLAwRo0aRWpqao5l9u3bR7du3fDz86NmzZq89dZb19Ty008/0aRJE/z8/GjRogUrVqxw+/4KgiAIgjtJyEjgpdUv0eCDBszfNR+bYuOORnew59E9fHvXt6VOeIWcsQP/xdWnxmKDzR/CF7c5hNdKdWDUKrjhUY8KrxabnROXHGMIcb4KFQERXz1A9jtL7o4AyMgv81WT1bVQyJv8PsOS4K7MV6fzNbokzldn7IBZMl89QYzrGDnE1zY1w6hXNRCjxc7v++N8WZpQSrErdmZsmEHPb3sSnxbPg2ENOKaPJDr+AFa1gSU1XuTO2JFc9/oW7vhgE+OX7GfB1rPsPX8Vs9VOqL+ONwe1oGWNMF/vilBGSUtLo1WrVnz00Ue5vv7WW28xZ84c5s2bx9atWwkMDKRXr14YjUbXMsOGDePAgQOsXr2a5cuXs2HDBsaMGeN6PTk5mdtuu43atWuzc+dO3n77baZOncr8+fNdy2zevJn77ruPUaNGsXv3bgYMGMCAAQP4999/PbfzgiAIglBM0sxpzNw4k3rv1+OtzW9htBrpUrMLG0du5Nf7fqVlREtfl5gnZpfzNXfjViipVP51BKyaCHYrNOsPj2yA6td7vLaTl9Kw2BQCDRoqSf9YoQIgsQMeIPudJZPVTqAhn4WLgMVmx2p33BUS52vxSc+cil9qM1+TMp2voW6IHRDnq0fInvkKoFKpGNS2Bm+tPMKinee5p31NX5YnlDIupV3i/p/vZ9XxNQTZbuSdgHAeTlyLBjsn7FE8YXqaw8drAcmA41zSonooLaqHcl3mf2uFB0gzN6FE9OnThz59+uT6mqIozJ49m0mTJtG/f38AvvnmGyIiIli6dClDhgzh0KFDrFy5ku3bt9OuXTsAPvjgA/r27cs777xDdHQ0CxYswGw288UXX6DX62nevDl79uxh1qxZLpH2/fffp3fv3rzwwgsATJ8+ndWrV/Phhx8yb948L3wSgiAIglAwFpuFz3Z9xrQN04hLdZgrWlRrwcweM+nbsG+ZiIByxQ5or/XctVUf5VXDLILOXAGNAXq/Du1GedTtmh1ns61G1YJQqUxe2aYg+BIRXz2AWq1Cr1Fjttndmvuans3FmK/zVcTXPLHbFYyZweOlN/PVIb5Gh0rsQGkle+ark7vb1OCdP46w7XQCpy+nUadKoK/KE0oRm85uYsiiIcQmJ9HCMp4P1eu40fQnAIttXXlLM4b69SJ4JFNobVnDIbSWhQG9UDpISUkhOTnZ9dhgMGAwFO2u76lTp4iLi6Nnz56u50JDQ+nYsSNbtmxhyJAhbNmyhbCwMJfwCtCzZ0/UajVbt27lrrvuYsuWLdx4443o9VkWll69evHmm2+SmJhIpUqV2LJlC+PGjcux/V69el0TgyAIgiAIvsCu2Pnh3x945a9XOJF4AoC6YXWZfvN07mtxH2pV2Zk87NQicoivdjtsfp951mloVXaMIXXxu+8biPKug/dInGPs0igiGLji1W0Lgi8Q8dVD6LWZ4qvFfUKoMXO6vEatQqe59sLc5XyV2IE8MWYTw0ut8zVzSrt7nK8SO+BujBYbl1PNANSolCW+Rob60a1hVdYfvcTiXed57rbGvipRKAXYFTtv//02E9dORGWL4F77k8zWfks1VRIWtYEDbabQrvMI/hGhVSghzZo1y/F4ypQpTJ06tUjriItzOHoiInJ2Z46IiHC9FhcXR7Vq1XK8rtVqCQ8Pz7FM3bp1r1mH87VKlSoRFxeX73YEQRAEwRcoisLK4yuZsGYCe+P3AlAtsBqTb5zM6Laj0WvK3tx4pxZh0GZe96Zdhp8fheOr0QK/2DoT2XceHaNqe722I3GOvNfGEUGQ4PXNC4LXEfHVQxi0alJN7hVCXc22dJpcL9ad4qu7c2bLE9ndw35az2S+ppis2OwKmmJMETZabCSmO5yzJXG+Bhmcma/ifHU3TtdroF5DqH/OxkeD2tZwiK87z/Nsz0YyTbyCciX9CsOXDue3Y78RYGvJ60ornlTPRa1SMFZqhN9939K6WhNflymUEw4ePEj16tVdj4vqehUEQRCEis7mc5uZsGYCG85sACDEEMKLnV/k6RueJkgf5OPqio8rdkCnhtN/w+JRkBILWj/e14/mvYQb+EpV/GvOknAk3ul8DeKKiK9CBUDEVw/htPa70/nqahSVh2NTYgcKxilg++nUbhfGnM5XgFST9RphrjA4Iwf8dRpC/Iv/5xmgF+erp4hJymq29d+bILc2iyDYT0vMVSNbTl6hS4MqvihR8CH/nP+Hexfdy9mrZ2lsv5UvSaaT5hcAMq4biv+d74I+wMdVCuWJ4OBgQkJCSrSOyMhIAOLj44mKinI9Hx8fT+vWrV3LXLx4Mcf7rFYrCQkJrvdHRkYSHx+fYxnn44KWcb4uCIIgCN7i34v/MnHtRJYdWQaAQWNgbIexjO86nioBZX8cb7LaUGPn7pSF8PU3oNihSiMY/BV/LUqChCSfaAepJivnEhzXVA2rBXHlkNdLEASvU3YCS8oYzo6Cnsh8zS3vFaThVmFwCthOcdKdGLQal+he3NxXZ+RAVJhfiaYiB0nmq8f4b7Ot7PjpNNzZKhqARTvPe7UuwbcoisJ7W96j25fdOJt0ngdUQ9jEITqpD2FS+WG+cx7+g+aK8CqUSurWrUtkZCRr1qxxPZecnMzWrVvp1KkTAJ06dSIpKYmdO3e6llm7di12u52OHTu6ltmwYQMWS9Zv4OrVq2ncuDGVKlVyLZN9O85lnNsRBEEQBE9zJukMI5aOoOXcliw7sgy1Ss2oNqM49uQx3rntnXIhvAKo0y7xte4N7kr6yiG8thoKY9ZBRHPXdasvIguPZTbbqhpsIDyw7MU5CEJxEPHVQzhdqO6MAHBmvhYkvlok8zVPChKwS0pwZtOt4ua+xiY5nK9RJch7hazM1wyLDZtdKdG6hJzk1mwrO4Pb1QTg939jSTaWrPmaUDZIMiYx8MeBjFs1Dmx65qvv5Cvb71RRJXM5sCH6xzeiv/4+X5cpVHBSU1PZs2cPe/bsARxNtvbs2cPZs2dRqVQ888wzzJgxg2XLlrF//34efPBBoqOjGTBgAABNmzald+/ejB49mm3btvH3338zduxYhgwZQnS046bT0KFD0ev1jBo1igMHDvDDDz/w/vvv52iw9fTTT7Ny5UreffddDh8+zNSpU9mxYwdjx4719kciCIIgVDAupl3kmZXP0OjDRny992sUFAY2HciBxw/w2Z2fUTO0pq9LdB8n13P75nvopvkXk8oPBsyFu+aC3tEU2JfGrSNxDvG1SWSw17ct+J4NGzbQr18/oqOjUalU1zRdVRSFyZMnExUVhb+/Pz179uTYsWM5lklISGDYsGGEhIQQFhbGqFGjSE1NzbHMvn376NatG35+ftSsWZO33nrL07uWLyK+egiDzv0nM9eU+TxiBwzifC2Q9MwMVHc323LijAoorugWl+wUX0uWvZN9/9Il99Wt5Od8BWhVI5QG1YIwWuys2BfrzdIEH7AzZifXf3I9Px/+mQZUZ6uqGaPta1GrFM7Wu5cqz2xEVbWRr8sUBHbs2EGbNm1o06YNAOPGjaNNmzZMnjwZgBdffJEnn3ySMWPG0L59e1JTU1m5ciV+flk3AxcsWECTJk3o0aMHffv2pWvXrsyfP9/1emhoKKtWreLUqVO0bduW5557jsmTJzNmzBjXMp07d2bhwoXMnz+fVq1asWjRIpYuXcp1113npU9CEARBqGgkm5KZum4q9efU5/2t72O2mbml7i1sfXgri+5ZRJMq5SiL326Dv16Hb/oTYL7MEXsNPmowH1oPzbGYwYf9Yg5niq+NI0R8rYikpaXRqlUrPvroo1xff+utt5gzZw7z5s1j69atBAYG0qtXL4xGo2uZYcOGceDAAVavXs3y5cvZsGFDjvFmcnIyt912G7Vr12bnzp28/fbbTJ06Nce41dtI5quHyDqZuS92wDVlPi/nq8Z3UwfKCk4B21Pia0mdr8480ZI6Xw1aNVq1CqtdIc1kc9UllJzzBThfVSoVg9rW4I3fD7No53mGdKjlzfIEL6EoCh9v/5hxq8ZhtpkZrm/He6YYKnGUNPy5csvb1LrxAV+XKQguunfvjqLkPRNCpVIxbdo0pk2blucy4eHhLFy4MN/ttGzZko0bN+a7zODBgxk8eHD+BQuCIAhCCTFZTczdMZfXNr7G5fTLALSNassbPd+gZ72ePq7OAyTHwpLRcNrxO7y/Wn8Gnx3AvUH1r1nUkNl82hfGraOZsQONxPlaIenTpw99+vTJ9TVFUZg9ezaTJk2if//+AHzzzTdERESwdOlShgwZwqFDh1i5ciXbt2+nXbt2AHzwwQf07duXd955h+joaBYsWIDZbOaLL75Ar9fTvHlz9uzZw6xZs3KItN5EnK8ewnkyc+edJKdwmGfDLXG+Fki6q+GWh5yvmU23ipv5GnfVPc5XlUrlEphTJffVrTidrzXycL4C3NWmOmoV7DiTyKnLad4qTfASyaZkhiwewtjfx2K3mlng142vTEepRCrHNfUxjvxLhFdBEARBEAQfYbPb+HrP1zT6sBHP/vEsl9Mv0zC8IT8O+pFto7eVT+H1+BqY19UhvOqD4O7PWF5nAkYMrn402ZHYAcGdpKSkkJyc7PpnMpmKtZ5Tp04RFxdHz55Zf6OhoaF07NiRLVu2ALBlyxbCwsJcwitAz549UavVbN261bXMjTfeiF6flSncq1cvjhw5QmJiYrFqKykivnoI58nMZHGj+FrIzFdfTB0oK2Q13PKU+Op0vhZPfI256p7MV8hquiWxA+7DZldc0RDReThfASJC/LixUVUAFu0855XaBO+wN24v7ea348cDP1IXPfv1rRiasReAdWF3UeP5TVSu3dTHVQqCIAiCIFQ8FEXhl8O/0HJeS0b8MoKzV88SHRzN/Dvmc+DxAwxuPhi1qpxJIDYr/PkqfHc3pF+GiBYwZj20HOzSBZwzZLOT1aPGfTN1C8PlVBNX0syoVNCwmoiv5YVmzZoRGhrq+jdz5sxirScuLg6AiIiIHM9HRES4XouLi6NatWo5XtdqtYSHh+dYJrd1ZN+Gt5HYAQ/hih1wYwSAS3zNQzjUSexAgWTFDnjmq5+V+Vo8wTPuambsQFjJxVdn0y1xvrqP+GQjNruCVq2iWnD+x2hw25qsO3KJJbsuMO7WxmjUKi9VKXgCRVH4bNdnPLXyKYxWIw/51WS20Uqw+RTJSgDrm07hjnsfQaWS4ywIgiAIguBt1p9ez/g14/nn/D8AVPKrxPiu43myw5P460o2q7DUcvUCLB4FZx2OQNo9BL1mgs5xneIUX53aRHY80aOmMDhdr7XDA/DXa7C40awm+I6DBw9SvXp112ODweDDakonIr56CJf4anFj5qu5cM5XiR3Im/QCohtKSnAJnK8ZZhuJ6Y73RYWUfIAQ4HS+mrx7N7M8cyEpSxwvSEzt0bQaof46Yq8a2XziMt0aVvVGiYIHSDWn8thvj/Hdvu/QKbAopAUDk88AsE+pz8Ve8+jXuYOPqxQEQRAEQah4nEw/Sb//9eOPk38A4K/159kbnuWFLi8Q5hfm2+I8ydFV8PMjkJEA+mC4cw5cd3eORZyuVqfQmh2X89XLxi1Xsy2JHChXBAcHExISUuL1REZGAhAfH09UVJTr+fj4eFq3bu1a5uLFizneZ7VaSUhIcL0/MjKS+Pj4HMs4HzuX8TblzHNfevBI5msBzldXwy0RX/MkI3MKvudiB5yZr0V3mzqnswfoNS4HbUkIMjj2MU1iB9yGM+81r2Zb2fHTabizVTQAi3ae92hdguc4cPEA7T9tz3f7vqM+Wk4ENnEJrwvUd6CMXElPEV4FQRAEQRC8yvGE4zyw9AHGHR3HHyf/QKvW8li7xzjx1Ale6/Fa+RVebRZY9QosHOwQXqNawaMbrhFeIbvzNe/MV3fGJBaGo07xNULEV+Fa6tatS2RkJGvWrHE9l5yczNatW+nUqRMAnTp1IikpiZ07d7qWWbt2LXa7nY4dO7qW2bBhAxZLlilu9erVNG7cmEqVKnlpb3Ii4quH8ET+akYBzaIM4nwtkPQC3MMlxeV8NRXd+Rqb6aqMDPVzy9RlZ7SCxA64D6fztXpYQKGWH9S2BgAr/40juZg5wILv+HrP17T/tD2HLx/mYb9qHNRUpWZaDElKIJP9J3LzU5/Rqk61glckCIIgCIIguIXYlFge/+1xmn7UlB8O/gDAvc3u5dATh/j49o+JCo4qYA1lmKSz8GUf2DzH8bjDIzBqNYTXy3Vxp7Caa+xApiDr7cjCw/FO52vJXZJC2SQ1NZU9e/awZ88ewNFka8+ePZw9exaVSsUzzzzDjBkzWLZsGfv37+fBBx8kOjqaAQMGANC0aVN69+7N6NGj2bZtG3///Tdjx45lyJAhREc7zE9Dhw5Fr9czatQoDhw4wA8//MD777/PuHHjfLTXEjvgMTwhhBbULMoVOyCZr3lSkHu4pLgyX4vhfI3NbLYVHeqeTKIgiR1wO1nia+EyeVvWCKVhtSCOXUxl+d5Yhnas5cnyBDeRbknnyRVP8sWeLzAosDSkIf2THdNUdtobMjtsPO+N6UeVIMkyEgRBEARB8AZJxiTe+vstZv8zmwyrY0zeu35vbtPcxtgBY9HpdD6u0MMc/g2WPg7GJPALhf4fQdN++b4l39gBHxi37HaFY/ESO1DR2bFjBzfffLPrsVMQHT58OF999RUvvvgiaWlpjBkzhqSkJLp27crKlSvx88u6Bl+wYAFjx46lR48eqNVqBg4cyJw5c1yvh4aGsmrVKp544gnatm1LlSpVmDx5MmPGjPHejv4HEV89hPME587ugZL5WnKyGm55yPlqKH7ma+zVLOerOwjMjB0Q56v7cMUOVCqcQK5SqRjcrgavrzjMop3nRHwtAxy5fIRBPw3i34v/0kBRsyGoHlGZwus8az9WVB3F1w93oVKg3seVCoIgCIIglH8yLBl8sO0D3tj0BonGRAA61ejEzB4z6Vy9MytWrPBxhR7GaobVk2HrXMfj6m1h0JdQqXaBb3XOwtVr8okd8KJ2cD4xg3SzDb1WTZ3KhZtJKJQ/unfvjqIoeb6uUqmYNm0a06ZNy3OZ8PBwFi5cmO92WrZsycaNG4tdp7sR8dVDeDTzNS/xNfOkKuJr3mQ13PLMVz/E3yG+JhtL4nx1k/iauY9pIr66jaLGDgAMaF2dN1ceYdfZJE5cSqV+1SBPlSeUkO/3f8+Y5WNINacyRl+Zj+xatKkXSSSYZ82PkhDdnW8f6khoQDl3VgiCIAiCIPgYq93Kl7u/ZOr6qcSkxADQvGpzXu/xOv0a9UOlUuXIcyyXJJyCRSMhZrfjcaex0GMKaAtnAjBb844dyDJueW+W5OG4ZAAaVA1Cq5EETKFiIeKrhzB4IMDalfkqsQPFJt0Z3eCxzFfHn1TxnK8O8TWqEM2cCkNgZuxAmlliB9yBoihFdr4CVAvx46ZGVVl7+CKLd57nxd5NPFWiUEyMViPPrnyWeTvn4afAsuB69Eu5DFjYSVOeMD5OVK36fPdQB0L8RHgVBEEQBEHwFHbFzuKDi5n01ySOXjkKQO3Q2ky7eRrDWgxDo/bMdVyp48BSWPYkmJLBvxIMmAuN+xRpFa6GW7nEDviiX8xRiRwQKjAivnoITwihGQUIhxI7UDAZZocL1HOZr5nO1xJkvrovdkCcr+4kMd3i+huMKuIxGtS2BmsPX2TJrgs8d1tjNOqSN1QTslAUhe2nE6lTOYBqIUU7NscTjnPPT/ewO243jRU16wLrEJlyGQUV85W7eMt0F9fXqcIXI9q7GuoJgiAIgiAI7kVRFP48+ScT1kxgZ6yji3mVgCpM6jaJR9s9ikFbQbL2LUZYNRG2f+Z4XLMjDPwcwmoWeVWuzFfttde+Bh/EDhyOE/FVqLiI+OohXLEDFg9kvublfNWI87UgPN1wy+l8NdvsGC02/IrgsHVmvrqr4VZg5j6mm0V8dQcxmZEDVYIMRTquAD2aViMsQEdcspFNxy9zU6OqniixwrJk1wWe+2kvBq2a+2+ozaM31adqcMED9MUHF/PQsodINiXzqL4SH9i0aNMuY/GrzKPpj7LG3Jwb6oXz+fD2rpsZgiAIgiAIgnvZdmEbE9ZMYO2ptQAE6YN4vtPzjOs0jmBDBRLqrpyAn0ZA3D7H4y7PwC2TQFM8A4BzFm6usQMa7xu3joj4KlRg5GrSQ3jiTpJTOMxL+BHna8E4M189FTsQpNeiUoGiQLLRUmiRLsNsIyndEVXgbuerNNxyD+eLETngxKDV0L9VNF9vOcOinedFfHUjiqIwf8NJwHG+/XzTKRZuPcuDnWvzyI31Cc+lMZbZZuaFVS8wZ9sc/BVYHlib29MSARtJETfQL2Y45yyhdG1QhU8fbOexmzWCIAiCIAgVmcOXDzNx7USWHFoCgF6j5/F2j/Nyt5epGljBxsv7F8GvT4M5FQIqw13zoWHPEq0y39gBnXeNWyarjVOX0wBoHCHiq1DxkJRjD+E8mZncGGBdcMMtEV8LwukeDvBQwy21WkWQwZn7WnjR0+l6DdRrCPFzT22BBsf3JM0kma/uwNlsq0YxM3kHtXVMFfrjQBxXM8p5cwAvsuXEFY7EpxCg1zB32PW0qhlGhsXGJ+tP0u3Ntby76ghX07M+79NJp+n6RVfmbJtDM0XNSX+n8KridIun6HThKc5ZQuneuCqfDRfhVRAEQRAEwd2cu3qOh5c9TPOPm7Pk0BLUKjUjWo/g6NijvNf7vYolvFoyHKLr4lEO4bV2F3h0U4mFV8hqpqXPpbmVt5t1n7yUhtWuEOynLXKEmyCUB8T56iGcJzh3Ol+NLuFQGm4Vl3RXdIPn7juE+OlIMVpJLoLAFpct71Wlck8eaKDe2XBLnK/uoDjNtrJzXfUQGkcEcyQ+heX7YhjWsbY7y6uwfPH3aQAGXl+DPi2i6H1dJGsPX2TW6qMciEnmg7XH+WrzaR7uWo/IiEM8umI4SRlJPKEL5X27Dk1GIgRFsKv92wxZpcdss9OzaTU+GnZ9rvlYgiAIgiAIQvG4kn6FmZtm8uG2DzHZTAAMaDKAGTfPoHm15j6uzgdcOuqIGbh4AFDBjc/DTeNB4x6ZJsv5eu2YVu/lzFdXs62IYLdd7wpCWULEVw/hPMG5606SoiikF5BXKrEDBZOVm+u5r74z97UozteYTPE1upiuytyQhlvu5UJSOgDVi3mMVCoVg9rW4LUVh/hpx3kRX93AmStprDkcD8DwznUAx+fco2kEtzSpxh8H4pn951EOx6Xw3p9HsZGOv/ZmFgTvpG9GEmCGejezrvlrjF5yBovNTq/mEXxw3/Wu86kgCIIgCIJQMlLNqcz+ZzZvb36bZFMyADfWvpE3erxBp5qdfFydj9j7P1g+DixpEFgN7p4P9W922+oVRckSX3MZ1xq8rB1Isy2hoiPiq4dwd+arxaZgsyuAZL4WF6vN7nIFeyrzFSDE3xGInmwsivPV4aqMLGKn9vxwiq/pEjvgFmKSHAJ5ccVXgAFtqvPGysPsOZfE6ctp1KkS6K7yKiTfbDmDosCNjarSoFpQjtdUKhW9r4ukaQ0zA76exsW4drRA4SP1QepnJGFHje2ml1ldeShP/W8vVrvC7S2jmH1va3S5TM0SBEEQBEEQiobZZmb+zvlM3zCdi2kXAWgd2ZqZPWbSq36viumANKfBihdhz3eOx3VvhLs/g+AI924m22zYXBtuedn56my21UTEV6GCIuKrh8gSX90jfDnzXqEQma82O4qiVMwfs3zI8Rl6MMcxpATO1yi3Ol8zM1/NVvk+uAFn5mtJ3MlVgw10rl+Zjccus3xfDGNvaeiu8iocqSYrP24/B8DILnVyXeb3Y7/zwM8PcCX9Ck8FLuIdmxadYiFWCecp81hO/d2SxPS92OwKA1pH887gVmhFeBVKgN1uJykpqdDLh4WFoVbLd04QBEEoX9gVOwv3L2TyX5M5lXQKgPqV6jP95unce929qFUV9Lfv4iFHzMClw6BSOyIGbnwe1O6/Ns0uquYWpaV3s15REE7xtZE02xIqKCK+egjXyczinjtJxkzhUKtW5TkdNvvzZptd8gr/gzNyQK3K/e6fuwjxy3S+FiHzNTZT2HNn+Lgz89WuOIRnTzUZqwikm60kpJmB4me+OunXKpqNxy7z695YEV9LwOKd50kxWalXJZCbGuZsymC1W5ny1xRe3/Q6wQr87h9N74xUwIK9QU+21ptC7MbLXM7M8R3UtgZvDmyJRi03KISSkZSUxKzlu/ELLPjCwpiWwrg72hAeHu6FygRBEATB8yiKwopjK3h57cvsi98HQGRQJFNumsKoNqPQaXQ+rtBHKArs/g5WvADWDAiKhIGfQd1uHttkdh1Cp7l2jOvN2IEUo8VlZJHYAaGiImqMh3AKn+5qfuVqFJXPdPnsgqLZKuLrf8n+GXrSBVqczNdYp/PVjeJrgF6DSuX4rU8zifhaEmIyBwvBBi2h/iUbNPZqHsnEn/dzJD6FI3EpMgApBna7wlebTwMwoksd1NlE05iUGIYuHsr6M+tpraj5wxBFtYwUUGmg5xTUnZ5kgFpN3w52ftlzgQyLjfs71s6xDkEoCX6BwQSGhPm6DEEQBEHwKpvObmLCmglsOrsJgFBDKOO7jufJDk8SqK/AUVumVFj+LOz/0fG4/i1w13wIqpr/+0qIU4cwaNW5Xvtmb9bt6VmSR+NTAYgIMRAWoPfYdgShNCNqjIcwuNn56nRt+uUzXV6fbbqsxaa4ZbvliXQvNNuC4mW+Zomv7osdUKlUBOq1pJqspJmsVA02uG3dFY3zmQ7JkrpeAUL9ddzUqBp/Hopn+b4YGkc2LvE6Kxrrj17i1OU0gg1a7r6+huv5NSfXMHTJUC6mXuRZbRBv2/VoTCkQWhMGfQE1O7iW1WvVDG5X0xflC4IgCIIglBv2xe/j5TUv89ux3wDw0/rxVIeneKnrS4T7V/DZHXH7HTEDV447jAC3TIQuz4IXIodMmTNn85rxadA4dAVFcWgHeq3nxNcjrmZbIR7bhiCUdipo2IrnMeiyMlQUpeRCqDOvNCAf8VWtVqHNdG9J061rKcxn6A6K6nxNN1u5mhlREBXmPucrZO1rqqnwLlzhWpzTZErSbCs7/VpFAfDr3hi3nB8qGl9mul7vaV+TIIMWm93Gq+te5dZvb8WUepFVhkhmWdVo7FZo3Bce2ZBDeBUEQRAEQRBKxsnEk9y/5H5az2vNb8d+Q6PS8EjbRzj+5HHevPXNii28Kgrs+AI+7eEQXoOjYcRv0O05rwivkJX5aiigWTe4b7ZuXhyJSwak2ZZQsRHnq4dw3kmyK2C1K7nmrBQFZ+ZrfrED4DiJWs02EV9zweke9rT4WtTMV6frNVCvIdjg3j/JIIOWiykml+u3NJOYZib2qpFm0aXvjmiMG5ptZadn0wj8dGpOX0nn3wvJtKgR6pb1VgSOX0xlw9FLqFQwvFMd4lPjuf/n+/nz5J+0U9Ss0EdS1ZQGah3cOg1ueAyk2ZwgCIIgCIJbiEuNY8aGGczfOR+L3XG9c0/ze5h+83QaVW7k4+pKAcZk+PVpOLDE8bhhLxgwFwIre7UMl/hamH4xVjt4cJLkkXhptiUIIr56CKfzFRwnM10JO2g7xTO/Qoiv6WYbZlvpF9u8TbrZ4f7097jz1SG+Ftb5GueMHAjzd3vWTmCmmJtWBpyvj363k62nEvjr+e7UrVK6cqEuuDF2ABzHpUfTCH7bF8uv+2JEfC0CX212dMzt2TSCUynbue+r+4hNieUFTSAz7Xo05jQIqw2Dv4TqbX1crSAIgiAIQvngqvEq72x+h1n/zCLdkg7AbfVv4/VbXqdttIy5AIjZ44gZSDwFai30mAKdxnrN7ZqdgmIHNJmzZq12BZPVs9rB8YuOzNfGIr4KFRiJHfAQ2fNXTW5woWYU1vmqccYdiPP1vxT2MywpIf4OwbOwma9OV6U7m205cbp808ylX3w9fSUNgLMJ6T6u5FrcHTsA0K+lI3pg+d4Y7HaJHigMV9MtLN55AQBD8N/c8s0tGFNiWaOvxls2DRrFBk3vdMQMiPAqCIIgCIJQYjIsGby7+V3qzanHjI0zSLek06F6B9Y8uIY/7v9DhFdwxAxsnQ+f3+oQXkNrwsiV0OUpnwivkKUH6PNpwu1quuVB7cBuV7iSZgYgIlR6kAgVF3G+egi1WoVeo8Zss7vlTpKxkFPmnQ5biR24lnQvxQ4U2/nqAfE1qAw5X1MzP6+UIjQq8xbudr4CdG9cjSCDlpirRnadTaRdnQqci1VIfthxlgyLDYPhCh/tfYYb0PCrLoIq5gzQ6KHX69D+YYkZEARBEARBKCFWu5Wv93zN1PVTOZ98HoAmVZrw+i2vM6DJALfP2CuzZCTBsrFw6FfH48a3Q/8PIcC3Y3tzAbEDztfSPRxZmGq24mxx4YznE4SKiIivHkSvzRRfLSU/mTmnzPsVIBwavHD3qqzizHz113v2ax+S2XCrsJmvMZnia2So+4Q9JwGZ4muqqXTHUNjsCmmZxye1kKK1t7DY7MQlO45RDTc6X/10Gm5rFsGS3RdYvi9WxNcCsNkV5m88CkCs/Tsm6AKYoehRWzKgUl0Y/BVEt/ZpjYIgCIIgCGUdRVFYcmgJE9dO5MiVIwDUDKnJq91f5YFWD6BVi4Tg4vxOWDQCks46+g3cNh06PloqjAAFZb5ClvPVk7Nmr6ZbXHUUFKEoCOUZiR3wIC4h1A3dAzMyBdzCNNxy1zbLG87YgQAPn/SdztdUs7VQ08njrmY2c/KI89Wxr+ml3PmaPRYhtZTVGp9sxK44Ij2qBLl3qky/VtEALN8Xi02iB/JEURTG/jyfyyl2QrjAMr+9vG7Xolbs0PxuR8yACK+CIAiCIAglYu2ptXT8rCODfhrEkStHqOxfmXdve5ejTx5lZJuRIrw6URTY8hF80cshvIbVhlF/lKpGr87Zt4Z8rn29Ib46o/hC/cX1KlRs5OzpQZziqzucr4XOfBXna554r+GW489KUSDFZC3whybW5Xx1v/gamOnyTS3lma/Z3a6FjWvwFs7IgagwP9Rq9w6mujSoQliAjsupJraevELnBlXcuv7yQGJGIiN+GcHWfZ3opkrlI7/3qGYxgsYAfd6EtiNKzSBXEARBEAShLLIzZicT1kxg9cnVAATqAhnXaRzPdXqOUD9pDJuD9ARY+jgc/d3xuFl/uPMDKGWfU2Gcr4bMPFhPagdXM2eDhoj4KlRwRHz1IM67TG7JfLUULq9UL5mveZLuih3wrPjqp9M4IiesdlKMlkKLr9FunNLuxBk7kF7KYweyu11Lm/PVE822nOi1avpcF8n3287x674YEV//w/YL27ln0T3EJMB0VTXG6RahVexQuaEjZiDyOl+XKAiCIAiCUGY5cvkIr/z1Cj8d/AkAnVrHo+0eZWK3iUQERfi4ulLI2a2w6CFIPl/q+w2YMvWDfGMHNJ6fNZuc4bi2E+erUNGR2AEPYnCjjd+V+SqxA8XGmfnq6dgByAoTd/7Y5EW62eq6G+gJ56szdqC0N9zK7nYtbZmvrmZbHhBfAfq1dEQP/P5vnNw0yURRFOZsnUOXL7qQlniGP1WBvKj7Ea3KDi3vhTHrRHgVhApKRkYG6enprsdnzpxh9uzZrFq1yodVCYIglC0uJF9gzK9jaP5xc346+BMqVDzQ8gGOjD3CnD5zRHj9L3Y7bJoNX/ZxCK/h9eDhP6HD6FIpvEKWBqEvTOarxXNGHWcfFGdfFEEoC3hivCl/AR7EnREAGebMzNeCnK9eyG0pq7iiGzzsfAXHj8vlVBMpxvybbjldr0EGrUe6PwY4YwdKufhaJpyvlTwjvnasV5kqQQYup5r4+/hlbm5SzSPbKStcNV5l1LJRLD60mO6KhsWaKoTbzpGh6InvNoM6PcaU2kGuIAiep3///tx99908+uijJCUl0bFjR3Q6HZcvX2bWrFk89thjvi5REASh1JKQkcAbm97gg20fYLQ6rkP6NerHa7e8RouIFj6urpSSdhl+fhSOOyIZuG4Q9JsNhmCfllUQZlfsQN7Xvu7sUZMXzsxXiR0QyhKeGG+K89WDZDlf3Rc7UGDma+bUAYs4X6/BGTvgFCQ9SXDmj0tyAS7O2CTP5b2CQ9SFrH0vreTIfC2t4quHnK8atYo7WkYB8OveGI9so6ywO3Y3bee35eeDi5mKH2sIItxm4qi9Os9Xmk1tEV4FocKza9cuunXrBsCiRYuIiIjgzJkzfPPNN8yZM8fH1QmCIJRO0sxpzNw4k3rv1+PtzW9jtBrpWqsrm0ZuYtl9y0R4zYszm2FeV4fwqvWDfu/DwM9KvfAKhct89Ua/GOcsT4kdEMoSnhhvivPVgzjvMrnDhVpY16Y03MobV+yAl5yvQCGcr5nNnDwkvgYayorzNetzKugz8zaeFl8B+rWK4qvNp1l1MB6jxVZgvEh5Q1EUPtn5Cc+sfIZKVjMbtOF0sVoBhWXqW3jR+AAzb+qASoRXQajwpKenExzsuOhdtWoVd999N2q1mhtuuIEzZ874uDpBEITShcVm4bNdnzFtwzTiUuMAaBnRkpk9ZtKnQR8ZW+WF3Q6b3oW/Xocy2m/AaQAz6PJruOX5WbNZsQMivgplB0+MN8X56kFcJzOL+zJfC3S+iviaJ4XNzXUHWZmvhYsd8Jj4qpfM15KgKAoxHo4dAGhTsxLRoX6kmqysO3LRY9spjaSYUhi2ZBiP/fYY3axWDmoyhVddIDuvf4On0h8mKCiEvi2ifF2qIAilgAYNGrB06VLOnTvHH3/8wW233QbAxYsXCQkJ8XF1giAIpQO7Yuf7/d/T9KOmPL7iceJS46gbVpfv7vqO3Y/spm/DviK85kXqRfjublg7wyG8thxSJvsNmAoROyDOV0HIHU+MN0V89SB6N8YOZGQKuAWJrwYRX/Mk3YvO12CX87WA2AGX+OoZYS+wrMQOlNLM1ytpZowWOyqV544RgFqt4o5WjsZbv+6L9dh2Shv74/fT7tN2/Lj/e15T/FhFIJVsFqjWHMasY/q5lgDcf0OtfAeOgiBUHCZPnszzzz9PnTp16NixI506dQIcroQ2bdr4uDpBEATfoigKK4+vpO38tgxdMpQTiSeICIzgwz4fcnjsYYa1HIZaJRJAnpxc74gZOPkXaP2h/8dw9ydgCPJ1ZUXGaQDLL3bAOb72pHbgjOEL8ZdJ10LZwRPjTfkL8CDutPEbzYWLHdBpPB+aXVZx5uZ6JXbAlfkqsQOFIbWUOl8vJDqOT7VgQ76dQt1Bv5bRzN9wkjWH4kkzWV3Hrrzy5e4veWLFE4RbjGzSVOIGW+YNgrYjofdMdsca2XPuGHqNmmEda/u2WEEQSg2DBg2ia9euxMbG0qpVK9fzPXr04K677vJhZYIgCL5ly7ktTFgzgfVn1gMQYgjhxc4v8vQNTxOkL3vioVex22D9W7D+TUCBqk0dMQPVmvi6smLjih3IL/NV4z6zWF6I81Uoi3hivFm+r+59jE8yXzXifM2L9EIK2O4g2FA452uc0/nqoTzRQINjX52RC6WVHM5XsxW7XUGt9v1UKG/kvTq5rnoIdSoHcPpKOn8eiqd/6+oe36YvSDOn8cSKJ/h679f0VrT8T12JUJsV9MGOzrEtBgHw1ebDANzRKoqqwQYfViwIQmli7dq1dO7cmcjIyBzPd+jQwUcVCYIg+JYDFw8wce1EfjnyCwAGjYGxHcYyoesEKgdU9nF1ZYCUOFj8MJze6Hjc5gHo8xboA3xbVwlxmrF83XBLMl+FsognxpsivnoQZ7i1O8RXl3BYyMxXT4Zml1WyGm55/mtfWOerM0/U085Xi03BZLWV2qnbKdnEV0WBdIuNoFLg/HQen2gviK8qlYp+raL5YO1xft0bWy7F10OXDjH4p8EcuXiAN/HjRfRgt0JkS4e7oHJ9AOKTjfyWGb8wsnNdH1YsCEJp484778RqtdK+fXu6d+/OTTfdRJcuXfD39/x5WhAEoTRxJukMU9ZN4Zu936CgoFapGdl6JFNumkLN0Jq+Lq9scHwNLBkD6ZdBF+gwArS8x9dVuYWs2IG8r/9cM3U9OGvW6XwNEeerUIbwxHhTAl88iDtt/M4p84VuuCWxAzlQFIX0Qn6G7qAwma9pJqsrA8dT4mtAtn1NM5Xe3Nf/NgQrLdED5xM932wrO/0yc1/XH73I1fT8hfuyxnf7vqP9p+1JvniQzeowh/AK0H40jFrtEl4BvvvnDFa7QrvalWhRI9RHFQuCUBpJTExkzZo19OnTh23btnHXXXcRFhZGly5dmDRpkq/LEwRB8DiX0i7xzMpnaPRhI77e+zUKCgObDuTA4wf47M7PRHgtDDYrrJkG3w10CK8R18Ej68uN8ArZGm7pfOx8NUrsgFD28MR4U8RXD+I80ZX0ZKYoiit2oKC8Um+cQMsiZpsdm10BvBM74JxW4ZxmkRvOZltBBi3BHpqGodWo8cv8Hv5X4CxN/FdsTTWVDuHRGTtQwwvOV4BGEcE0jgjGYlP442CcV7bpaTIsGYz5dQwP/PwAt5hN/KsOo73dDoZQuOcbuP0d0GXdfDBabCzcehaAkV3E9SoIQk50Oh1dunTh5Zdf5o8//uCff/7hvvvuY9u2bcycOdPX5QmCIHiMFFMKr657lXpz6vH+1vcx28zcUvcWtj68lUX3LKJJlbKbT+pVrl6Ar/vBxncBBdo9BA//CVUa+royt1KozFcPz5o1WW0YMx244nwVyhKeGG/6fl5vOcZdma/ZhUM/yXwtFkZz1ufhjYZbhXG+uvJePeR6dRJk0GK0mEkrxbmv/20IllxKnK8XvOx8BejXKoojq1L4dW8M97Qr286FY1eOMfinwRyM28ss/HgWvaOhQfT1MOgLCL9WXP11bwxX0sxEh/rRq3mED6oWSiN2u52kpKRCLx8WFoZaLfeXyyNHjx5l3bp1rFu3jvXr12MymejWrRvvvPMO3bt393V5giAIbsdkNTFvxzxmbJzB5fTLALSNassbPd+gZ72ePq6ujHF0Ffz8CGQkOPoN3Pk+XDfQ11V5BJfzNd/YAcdrntIOkjMc13QqVVZPFEEoC3hivCl/AR7ElaFiKdnJLLtwWNCUeYM4X3Ml3eI48es0KnQaz1+QFybzNeaqQ9iL9LD46si4NZfq2IH/itSlJXYgq+GW9wL372gZzTurjrL5xBUup5qoElQ2m039eOBHHl72MJVNqWxRh9I28wYSNzwOPV8Frf6a9yiKwpd/nwbggU510Hrhb1UoGyQlJTFr+W78AoMLXNaYlsK4O9oQHh7uhcoEb9OkSROqVq3K008/zfjx42nRogUqle8bNAqCILgbm93Gd/u+Y/K6yZy96pgV1KhyI1675TUGNh0o576iYLM4YgY2z3E8jmoFg77MEXtV3nBqEHofNtxyXgsHG7SlopmyIBQWT4w3RXz1IFk2/pKJXs7IAa26YOHQuU2LZL7moLANy9yF0/man4PT6XyNDvWsq9LZdKtUxw5k1hYeqCchzXyNE9YXpJqsroD46DDPCuTZqVMlkJY1Qtl3/iq//xvHAzfULvE67XYFq13Jd/DlLkxWE8+teo6Ptn/EXYqWr1WhBNvt4BcGA+ZCk755vnfbqQQOxibjp1MzpH3Zdv0K7scvMJjAkDBflyH4mKeeeooNGzYwbdo0li9fTvfu3enevTtdu3YlIKBsd6YWBEEAx83oZUeWMXHtRA5cOgBAdHA0U2+aysg2I9Gq5RK+SCSdg0UPwfltjscdHoHbpoO2bBocCouzB0zhYgc8Y9KRZltCWcUT4005c3sQd9n4neJrYbJKpeFW7mSYC/8ZugPnD4zZasdoseGXi+gb6yXna5DBse3SKr4qiuISWyND/BziaylwvsZkul5D/DyXyZsXd7SMYt/5qyzfG1Ni8TXdbOXBz7dxKDaZF3o15sFOdTx25/lk4knu+eke9sfsZA5+PIkeFDvUaO+IGQirle/7na7Xu9pUp1Lgtc5YQRCE2bNnAw439MaNG1m/fj0TJ07kwIEDtGnThr///tu3BQqCIJSADWc2MP7P8Ww5vwWASn6VmNB1AmM7jMVf570YrHLD4RWw9DEwJjn6DfT/EJrd6euqvILJ4sx8zS92wMPO1wxptiWUTTwx3pQ5nR7E4KYA6/TMrM7CuDb1GvfkzJY3nM5XxxR8zxOk1+J0peeV+xqTlOl89bCr0rnPaebSGTtgtGRlGjvzb1NKgVCclffqfSfV7S2jAdh2OsHlkC4ONrvC0//bw44ziaSZbUz99SD3ffoPZ6+ku6tUF0sPL+X6T64nKWYXW1UhDuEVoMvTMPL3fIVXm11hwdYzrMpsMjaiszTaEgQhf2w2GxaLBZPJhNFoxGQyceTIEV+XJQiCUCz2xO2h74K+3PTVTWw5vwV/rT8vd32Zk0+f5IUuL4jwWlSsZlg5Af53n0N4jb4eHt1QYYRXyJb5qstb8jF42Ljlcr562cgiCO7CneNNEV89iPNEV1Ibv7E4zlcRX3Pgcg97KXZArVYRZHBGD+Se+5rVcMuzg6mgUh47kGJyfD4qFVQLcYivpcH5et6V9+r9wW71MH/a1a6EosBv+2OLvZ7XVxxi9cF49Fo1j3WvT4Bew9ZTCfR+fwPfbDmN3ZnDWgLMNjPj/hjHXT/cRS9jGntVobRWAP9wGPoT3DoNNHkPuLacuMIdH2xi4s//Ylegz3WRNI4sONdTEISKyVNPPUXLli2JiIjgkUceISYmhtGjR7N7924uXbrk6/IEQRCKxPGE4wxdPJQ2n7Th9+O/o1VreazdY5x46gSv9XiNML8wX5dY9kg8DV/0gn8+djzuNBYe+gMq1fFlVV4nq+FWPrEDGvf0qMkLZwSfOF+FsoYnxpsSO+BBXCezksYOZDbcKpTzVcTXXMnIdA8HeCl2ABx3+FKM1rydr5mxA1Eeb7jl2OfSkKOaG06hNcigJSQzKzfVlHejMm/hdL7WqOQbp0G/VtHsOJPIr3tjGNW16E7Qb7ec5vNNpwB4d3Ar+rWKZmiHWrywaC//nExg8i8HWLE/lrcHtaJmePHcvWevnuX+X+5nz7l/mIsfjzpjBmp1goGfQ2j1PN97LiGd1347xMoDDrdriJ+WZ29txP1uyLgVBKH8Ehsby5gxY+jevTvXXXedr8sRBEEoFrEpsUzfMJ1Pd32K1e4YCw+5bgjTb55Og/AGPq6uDHNwGfwyFkxXHf0G7poHjfv4uiqf4DSA5Rc74OnIwmRX5qvITkLZwhPjTZ87Xz/66CPq1KmDn58fHTt2ZNu2bfkun5SUxBNPPEFUVBQGg4FGjRqxYsUKL1VbNAw672e+6jSOue6S+ZqTdC9nvkK2plsZ1wqJqaYsUTbKw85KZ8MtZ3xFacMpCgcbtC6XbmkQimN86HwF6NMiErUK9pxL4lxC0WIC/jp8kSnLHA0aXujVmH6tHDEGNcMDWPjwDbx6Z3P8dRr+OZlAr9kb+LYYLtgdV3fQ4YsOJJzbxnZViEN4RQXdnoPhy/MUXlNNVt5aeZges9az8kAcahU82Kk261+4mZFd6hbYVFAQhIrNTz/9xNixYz0ivJbnMakgCKWDJGMSL695mfpz6jN3x1ysdit9GvRh9yO7+X7g9yK8FherEVa8AD8+4BBea3SARzdVWOHVblew2Bxj+/wa7rqrR01eSOarUFbxxHjTp1e5P/zwA+PGjWPKlCns2rWLVq1a0atXLy5evJjr8mazmVtvvZXTp0+zaNEijhw5wqeffkr16nm7q3yJLzJfPR2aXVZxia9eih2ArGyb3JyvcZmu1+yCo6fIih0onZmvLuern5Ygp2BdCmIHLmSKr9E+El+rBfvRqX5lAH7dF1Po9x2MSWbswl3YFbinXQ0e714/x+tqtYrhneuw8pludKgbTrrZxiu/HGDYZ1sLJfJa7VZe/utlZpyaQZ/0FHargrlOAQKqwP2Locdk0Fz7nbbbFRbtPM8t76zj43UnMFvtdGlQmd+fvpFp/a+TBluCIBSab7/9li5duhAdHc2ZM2cAR2OEX375pdjrLO9jUkEQfEu6JZ23/n6Leu/XY+ammWRYM+hUoxPrhq9jxbAVtI5s7esSyyyBpni0X/WBbfMdT3R5GkaugLCavi3Mh2Q3YuUbO+AmvSIvJPNVKMu4e7zpU/F11qxZjB49mpEjR9KsWTPmzZtHQEAAX3zxRa7Lf/HFFyQkJLB06VK6dOlCnTp1uOmmm2jVqpWXKy8cWeKrmzJfi9BwS8TXnGS4Gm75wPmaS+ZrrDPv1cPNtgACDI59Lr2Zr1mxAy7na2kQX10Nt3zX4KBfZuOtX/cWLvc1PtnIqK+3k2a20bl+ZWYMaIHK2fntP9SuHMj/Rt/A1H7N8Ndp2HLyisMF+8+ZPF2wF5IvcMvXt/DR5nf4TPHjO/wJUBSo0w0e+xsa9Mj1fTvPJHLXx3/z/E97uZhionblAOY/0JbvRnWUfFdBEIrE3LlzGTduHH379iUpKQmbzfH7HhYW5upMWxzK+5hUEATfYLFZmL9zPg0/aMhLf75EojGR5lWb88uQX/j7ob+5qc5Nvi6xTKM6sISbDr+CKn4/BFSGYYsK7DdQEcie4VoY8dVjztfM6+DQgIp9PISyhyfGmz4L3zCbzezcuZMJEya4nlOr1fTs2ZMtW7bk+p5ly5bRqVMnnnjiCX755ReqVq3K0KFDeemll9BochfVTCYTJpPJ9TglJQUAi8WCxeLZXEk1jpOYyWIv0bZSM09aBq2qwPWocXwpTFabx/fPVzj3qyj7l2o0A44fH299LkGZomdSmumabZ67kgZARLDB4/X4ax3iW4rR89/5wpL9GF5Nc/x9Buo1paZWs9VOfIpDII8I0vqslh6Nq6BVqzgUm8yhC4k0qBaU57LpZisPfbWd2KtG6lUJZM69LVEpNiyW/G/+DOtQg64Nwhm/5F92nEnilaX/8vu+GF6/q3mOyIXVJ1czYtkIqqRdYYcqmGaKCgUV9m7PY+/6PKg18J/PKfaqkXdWHWPZPod4HKjX8Hj3egzvVBuDVo3V6nuRvaJSnPOoL7FYLCiKDbu94JuZimJz/caXlfcVh7Jy7NzNBx98wKeffsqAAQN44403XM+3a9eO559/vljrrAhjUsH9lLXzqHAtnjyGdsXO4kOLmbJhCscTjgNQO7Q2k2+czNDmQ9GoNTIOKgmWDNSrJ6Ld/Q0Athodsd/1GYREXTMerYikGh2/NRq1CsVuw5LHuETj1Cs8pB0kpTmuwQN0eV+Dy7k0b4oyrgTfjGWt1tyNPmUdT4w3fSa+Xr58GZvNRkRERI7nIyIiOHz4cK7vOXnyJGvXrmXYsGGsWLGC48eP8/jjj2OxWJgyZUqu75k5cyavvvrqNc9v2LCBgwcPlnxH8iE+A0BLaoaxRBlgey6oAA1X4mNZseJCvstezNxmuslc7nPHVq9eXehl/z2jBtTEXzjLihWnPVZTdhLiHNvc/e9hViTn/K5tPOc4ptbkSx4/TscvOrZ1+nzB3x9vs3r1arbGOupLSbzEwb0XAQ2xlxJ9+v29bARF0aJTKWxdv4Y8zKNeoVGImoNJat7/eRN9auZ+V9quwOdH1BxIVBOkVRhW8yp//1X4vw+AYVFQS6Xi17NqNp9MoNd7G+hfx07HqlZ+jP+Bn+J/4kFFy1yC8FfAqA1lZ53HuJzaDFb+kWNdZhusjVGxJkaN2a5ChUKHqgp31LISknKINasOFfvzENxLUc6jviQlJYUTF9T4BRbslDampbDaeILg4OAy877icPny5SItb7PZmDp1Kt999x1xcXFER0czYsQIJk2a5HLIK4rClClT+PTTT0lKSqJLly7MnTuXhg0butaTkJDAk08+ya+//oparWbgwIG8//77BAVl3Rzat28fTzzxBNu3b6dq1ao8+eSTvPjii8Xaz/9y6tQp2rRpc83zBoOBtLS0Yq2zIoxJBc9RVs6jQt648xgqisKelD18G/stJzNOAhCqDWVwxGB6Ve6F7pyOP879UcBahPwIMsbS7tSHhBrPoaDiaEQ/jlS5C2XTbmC3r8srFVwxAmjRYM/3msqpV6RlmDxy7XUuXgOoOPrvHlZcyP/YyLn0WooyrgTfjGW3xBRtPFpW8MR4s0y1nbPb7VSrVo358+ej0Who27YtFy5c4O23385zoDthwgTGjRvnenzhwgWaNWvGjTfeSJ06dTxa7/nEDF7fsxFFpaFv317FXs/RNcfh7Eka1qtN375N8102JimD1/ZsxI66RNsszVgsFlavXs2tt96KTle4KQw7lh+CmHM0bVSfvj0bFvwGN3D4z2NsjD9FRI1rj9vfSw/A+Qu0b96QvrfUz2MN7kFzIJ4FJ/YSGBpO374dPLqtwpL9GJ7ZfA5OH6dhnZrc0q4GHx/aikrvT9++N/qsvq2nEmD3DmqEB3L77V19VgeAJTqG5xf/y1FjMHP6dM41RuC1FYf5N/Eseq2aL0a2o02tsGJt6w7g8SvpjP/Z4YL98aSGn89fxW5pw/+0sdyj2QvAbm1rXlXGoCTWQnVVhbMilcrx/+cTM4hPcdxxb1srjEl9m3Bd9ZBi1SR4huKcR31JQkICpzaeJCA4rMBl01OSuLVbPcLDw8vM+4rD6dOni7T8m2++ydy5c/n6669p3rw5O3bsYOTIkYSGhvLUU08B8NZbbzFnzhy+/vpr6tatyyuvvEKvXr04ePAgfn6OmJxhw4YRGxvL6tWrsVgsjBw5kjFjxrBw4UIAkpOTue222+jZsyfz5s1j//79PPTQQ4SFhTFmzJhi7Wt26taty549e6hdu3aO51euXEnTpvmPkdxJWRuTCu6nrJ1HhWtx9zHcdmEbk9ZNYt2ZdQAE6YMY13EcT3d4mmCDxCy5A9X+H9H8Pg2VJQ0lsCqm2z/g8DGz/B3+h+MXU2H3ZgIMevr2vTnP5Zx6hb2EekVevHN4I6Rl0KNbJ67P4/pEzqV5U5RxJfhmLNuptne0FW/jifGmz8TXKlWqoNFoiI+Pz/F8fHw8kZGRub4nKioKnU6XYzpX06ZNiYuLw2w2o9df27DFYDBgMBhcj5OTkwHQ6XQe/+MO9HdGANjRarV5Zi8WhDmzU2GgoeCaA/wczjiLTSnRNssCRTmGRqvjMwzy03vtpB4W4PjepZrt12wzPsUxBaNGeKDH6wkNdNSRZraVuh80nU5HusVxbEL89VQKclzcp5qsPq01LsUx7aV6pQCff2a9WkTz8i8HOXk5jeOXjTSLzilifrPlNF9tOQvArHta0aF+1RJtr0FkKD880plJy/9k4eYU6ltS+VD3NQ3UMdgUFbOsg/nYeCcKakhLznM90aF+TOjblDtaRpXr81BZxxu/he5Ap9OhUmlQqwvO7VapNK79KivvKw7O96WkpLjGNnDtuMfJ5s2b6d+/P7fffjsAderU4fvvv2fbtm2Aw601e/ZsJk2aRP/+/QH45ptviIiIYOnSpQwZMoRDhw6xcuVKtm/fTrt27QDHtKy+ffvyzjvvEB0dzYIFCzCbzXzxxRfo9XqaN2/Onj17mDVrllvE13HjxvHEE09gNBpRFIVt27bx/fffM3PmTD777LNirbMijEkFzyHHr+xT0mN46NIhJq6dyM+HfwZAr9HzeLvHebnby1QNLNm4TMjEnA4rXoA93zke1+mGauBnaPwqw7EV8nf4H+wqR5arQafO93Nx6hVmW8n0irxw9vaoHOxX4PGRY3gtRRlXgm/GslptmfJzFhpPjDd99knp9Xratm3LmjVrGDBgAOBwEaxZs4axY8fm+p4uXbqwcOFC7HY7arXjhHL06FGioqJyHeT6GoPW8YW1K2C1K+g0xTuZZWRmNvoVpuFWtkBti01BrxXRA7I+Q2823Arxz7wwzrXhlqOZU2SoFxpu6R1/5unmkjV+8xSpJsfnE2TQEuxsuGWyoiiKz0Q7V7OtMN8123IS7KfjlsbVWHkgjl/3xeQQX/86fJGpyw4A8EKvxtyR2aCrJNgVOzM3vc5bu6cw2i+E2YAfdkz+1fj3hve4vlp75lqt7Nixk3Zt26LOFB4UQMns02XQqrmhXmX8vfj3JggVlWbNmuV4PGXKFKZOnXrNcp07d2b+/PkcPXqURo0asXfvXjZt2sSsWbMAx/SquLg4evbs6XpPaGgoHTt2ZMuWLQwZMoQtW7YQFhbmEl4BevbsiVqtZuvWrdx1111s2bKFG2+8Mce4rFevXrz55pskJiZSqVKlEu3vww8/jL+/P5MmTSI9PZ2hQ4cSHR3N+++/z5AhQ4q1zoowJhUEwf2cvXqWV9e9yld7v8Ku2FGr1DzY6kGm3jSV2mG1C16BUDguHoKfRsClw4AKuo+HG1/Itd+A4MCU2UDLqUfkhcE5ji+hXpEbdrtCcobj+IT4iagqlC08Md70qUw9btw4hg8fTrt27ejQoQOzZ88mLS2NkSNHAvDggw9SvXp1Zs6cCcBjjz3Ghx9+yNNPP82TTz7JsWPHeP31113T5Uob2TsLmqx2dJq8Ow3mh1M0K4xwmH2bZps9hxhbkckowmfoLoL9HH9eyRnXhunHXnU0c4oO87z4GpQpaKaZSmeof6rRUVeQQUtQ5mdmVxzf+0CDb05RF5LSAaheyffiK0C/VtEO8XVvDC/2aoxKpeJgTDJjF+7CrsA97WrwePeSx1dcSrvEAz8/wObjf/Ad/tyXGcJPg1sx3DWPtoFVAMf0INNJhR5Nq8kdakHwMQcPHqR69equx7m5XgHGjx9PcnIyTZo0QaPRYLPZeO211xg2bBgAcXFxALnmnjpfi4uLo1q1ajle12q1hIeH51imbt2616zD+VpJxVdwRB8MGzaM9PR0UlNTr6mpOJT3MakgCO7jcvplZm6cyUfbP8Jkc8QsDWgygBk3z6B5teY+rq4coSiwZwH89jxYMyAoAgZ+BnV9F01WVjBZnOJr/lqA3k16RW6kma3YM40ZTlOSIJQl3D3e9Kn4eu+993Lp0iUmT55MXFwcrVu3ZuXKla5B+tmzZ11uAoCaNWvyxx9/8Oyzz9KyZUuqV6/O008/zUsvveSrXcgXfbaTl9lqh9yvhwrEmOnaLIyLzF3bLG84BWx/vfe+8s47fMn/cb6mmqykZAqOkaGeF/cCDRrXdksjzrqC/LT46zSoVQ7xNdVk9aH4WnqcrwC3NKlGgF7D+cQM9pxLIirUn4e+2k6a2UaXBpV57a4WJXYJbzq7iSGLhlA1OZZdBNMAFag00GMydH4K1HIjRxBKI8HBwYSEFJyp/OOPP7JgwQIWLlzoigJ45plniI6OZvjw4V6o1P0EBAQQEBDglnWV9zGpIAglJ9Wcyntb3uPtzW+TYk4B4KbaN/FGzze4ocYNPq6unGFKhd+eg33/czyufwvcNR+CJMahMJisjmtfg67w4qu7tYOrma5XvVZdqBm8glBacdd40+cBDWPHjs1zSte6deuuea5Tp078888/Hq7KPajVKvQaNWab3XUCLA5O12ZhTlpqtQqtWoXVrjhOoAIA6U4B24snfqfz1Sm0OonLjBwI9tO6XKmeJDBTcDZZ7VhtdrRuvKPpDlKyOV9VKhVBBi3JRodAHeGjHk2u2IFS4nz112u4tVkEv+yJ4Yft59h/4SpxyUYaVAvi42FtS3SX2q7YeXfzu0z4cwJjFDWzCUIPEFIDBn0BtTq6bT8EQfAdL7zwAuPHj3dNlWrRogVnzpxh5syZDB8+3JVtGh8fT1RUlOt98fHxtG7dGoDIyEguXryYY71Wq5WEhATX+yMjI3PNTnW+Vhyuv/561qxZQ6VKlWjTpk2+N5t27dpVrG1A+R6TCoJQfMw2M5/s+IQZG2dwMc1xDmwT2YaZPWZyW/3bJNve3cT964gZuHIMVGq4eSJ0HSdGgCJQ2NgBjQe1A+fsz1BxvQrZsNlsTJ06le+++464uDiio6MZMWIEkyZNcp1LFUVhypQpfPrppyQlJdGlSxfmzp1Lw4ZZzb0SEhJ48skn+fXXX1Gr1QwcOJD333+foKCgYtfm6fGmz8XX8o5Bmym+Wop/MitqXqlOo8Zqt4n4mo0Ms+Pk74vM1/86X2OSHJEDUV7IewVyuEfTzDZC/UvXwCW78xUcGafJRqvPnLp2u0JMZixEaXG+AvRrGc0ve2L43/ZzAFQO1PPliPYlGtAkZCQwfOlwNhxZzvf4M5jMdTXqAwM+hoDidWEXBKH0kZ6ensO5CaDRaLDbHWOFunXrEhkZyZo1a1xia3JyMlu3buWxxx4DHGJjUlISO3fupG3btgCsXbsWu91Ox44dXctMnDgRi8XiiiVZvXo1jRs3LnbkQP/+/V1xCv379xehQxAEr2Cz2/j+3+955a9XOJ10GoAG4Q2YcfMMBjcfjFpVusbUZR5FgZ1fwe8vgc0EwdEw6HOo3dnXlZU5nOKrvhAGDb1WjdVsK5FZLDeuuvJeRXISsnjzzTeZO3cuX3/9Nc2bN2fHjh2MHDmS0NBQV3TTW2+9xZw5c/j666+pW7cur7zyCr169eLgwYP4+Tk0lGHDhhEbG8vq1auxWCyMHDmSMWPGsHDhwmLX5unxpvwleBi9Vg2mrBNgcXA6Xwvr2tRr1WRYbJhtpbPBki/IKEJ0g7twOl9TTVbsdgW12vHHG3fVKb56R9jTa9XoNCosNoU0k7XU3X10iqzOZltON3Cq0Tfi6+U0E2arHbXKOw3RCku3RlUI8XO4gg1aNZ8Ob0fN8OJPf9h6fiv3LLqHaknn2UMwdVGhqHWobn0VbngcRNwQhHJFv379eO2116hVqxbNmzdn9+7dzJo1i4ceeggAlUrFM888w4wZM2jYsKFrsBsdHe1qQtW0aVN69+7N6NGjmTdvHhaLhbFjxzJkyBCiox0N/4YOHcqrr77KqFGjeOmll/j33395//33ee+994pd+5QpU1z/n1szMUEQBHeiKAq/HfuNl9e8zP6L+wGICopiyk1TeKjNQ+g0pWssXS4wJsPyZ+DfxY7HDW+DAfMgsLJPyyqrOE1YBcUOgONaMd3sfuOW04BU2q49Bc+QkpJCcnKy67HBYMi1D8HmzZvp378/t99+OwB16tTh+++/Z9u2bYDj/Dt79mwmTZpE//79Afjmm2+IiIhg6dKlDBkyhEOHDrFy5Uq2b9/uagL7wQcf0LdvX9555x3XmLSoeHq8KbfrPIwz5LokJ7OMIk6Zd2a3lETwLW/4ouGWM/NVUSDVnCUkxmTGDnjL+QpZ7td0c+nLfU27xvnqFK19073UGTkQEeLn1tD5kmLQarj/htoYtGreu7c119cqnoNMURTe/+d9un3RjQFJcfxNEHVRQVgtVA/9AZ2eEOFVEMohH3zwAYMGDeLxxx+nadOmPP/88zzyyCNMnz7dtcyLL77Ik08+yZgxY2jfvj2pqamsXLnS5TIAWLBgAU2aNKFHjx707duXrl27Mn/+fNfroaGhrFq1ilOnTtG2bVuee+45Jk+ezJgxY9yyHw8//HCuEQCCIAjuYNPZTXT7shv9vu/H/ov7CfMLY2aPmRx/6jiPtHtEhFdPELsX5t/kEF7VWrh1Gtz3gwivJcCV+VqI5tsGD2kHLueriK8VgmbNmhEaGur652xQ+l86d+7MmjVrOHr0KAB79+5l06ZN9OnTB4BTp04RFxdHz549Xe8JDQ2lY8eObNmyBYAtW7YQFhbmEl4BevbsiVqtZuvWrW7ZH0+MN8X56mEMmYJpiTJfM8VXv0IKh87pBRI7kIWz4VaAzntfeT+dxpX5m5xhcYmx3na+giP3NSndQqqp9Lmhs2e+QpYI+9+sXG9R2pptZefF3k14umfDAvOb8iLJmMSoZaP46+ASfsSfAc6Ygab94M4PwT/MfcUKglCqCA4OZvbs2cyePTvPZVQqFdOmTWPatGl5LhMeHl7glK6WLVuycePG4paaL5cuXaJ3795UrVqVIUOGcP/999OqVSuPbEsQhIrDvvh9vLzmZX479hsAflo/nurwFOO7jqeSf/FueAsFoCiw/TP442WwmSG0pqPfQM0Ovq6szOOMPCzMNYOnjFvJGeJ8rUgcPHiQ6tWrux7n5noFGD9+PMnJyTRp0gSNRoPNZuO1115j2LBhAMTFxQG4Gp46iYiIcL0WFxdHtWrV/s/efYc3Vb5/HH9nd7fsjaCg7I2CgIIgKIoiiPJzgiiKIAJ+HaBMFRAVBw4cDBcOEGQpiOwpG0EQRabs1T2yzu+P9KQtlDZJk5ykvV/X5fX9pj05eUrS0+fc5z6fJ8/3jUYjpUuXdm9TVIGYb0rxNcD8cSUpw+p6rqddm/7oti1OFEXJVcAObidjXKSRc6nWPIXEE0nBzXwFiLa4PjvpGuWoXonV7nT/bsRaXH+Y3bEDGo011BbbupSvhdftJ7fTa3Yvyl04wg5iuAo9isGMrvPrcP0T0u0qhAgL8+fP5+LFi8yePZtZs2YxefJk6tSpw4MPPsgDDzxAjRo1tB6iECKMnMo6RZ8Fffh2z7coKBh0Bh5v9jgjbxpJlbgqhe9A+CYjERY8A/sWuB5f1xXu/lDWG/CTnAW3PIgdCFDjVrI781WKryVBbGwscXGFr5b9ww8/8M033zBr1izq16/Pzp07GTJkCJUrV+bRRx8Nwkg9E4j5ZujcU1tM5VxJKkLna/at4t7GDlgdUnwFyLQ5URTX/48yB/d6Q2z2H5vcxddTauxAQvBjB7QqaF5JWq4YBLVAHKtx5+uJ7M7XyiHY+eoLRVH4eMvH3Ph5a3pc+I+1RHMVeihVE12/ZXBDfym8CiHCSqlSpejfvz+rVq3iyJEj9OnTh6+++opatWppPTQhRJg4nXqaIUuHMOivQczaMwsFhfvr38++gfuYeudUKbwG0vFt8MlNrsKr3gRdJkDvWVJ49SN37IAHma9qY4e/awfJ2edy0vkqcnv++ed56aWX6N27Nw0bNuThhx9m6NCh7piCihUrAnD69Ok8zzt9+rT7exUrVuTMmTN5vm+327lw4YJ7G3/w93xTOl8DrKhdqLm7Nr0uvkrnK5AT2wCe/xv6i7q6o3rlD+Bkogadr9lF57QQy3xVi8GRJgPG7Kuumne+hnDsgLdSslJ4YuET/LbnB+YQwZ1qzED9HtDtPYgo/OqkEEKEKpvNxtatW/n99985fPjwZbeoCSHEpZIyk3hrw1u8s+kd0mxpANxa81YmdJpA88rNNR5dMacosOljWDYKnDZIuAp6zYAq8u/ub2rnq9ngReyAzb/xdDmZr1JyEjnS09PR6/NeFDAYDDidrs9szZo1qVixIsuXL6dJkyYAJCcn8/vvvzNgwAAAWrduTWJiItu2baN5c9fxY8WKFTidTm644Qa/j9lf802//iZkZGQQGRn+BQt/Uq8k+Ro7YHU4cWZ3bXqb+WqTzlcgZ5Epi1GPQR/cDj9352v24lEpmTZSsouKFYOZ+ZrdVZoWYpmvqZmu8ag5rwAxlsu7hYPpvxCPHfDUH6f/cMUMnPuXnURTFT2KwYLu9onQvK90uwohwtbKlSuZNWsWP/74I06nkx49erBo0SJuueUWQOajQojLZdoz+XDzh4xfN54LGRcAaFm5Jd0iu/HS/S9hMkl3XkClX4D5A2H/z67Hde+Cu6bIegMBojZhedL5Gqi7ZiXzVeSnW7duvP7661SvXp369euzY8cOJk+ezGOPPQa41h8YMmQIr732GrVr16ZmzZqMHDmSypUr0717dwDq1q3LbbfdxhNPPMHUqVOx2WwMGjSI3r17U7lyZb+NtbD5prf8UnzNysrigw8+4M033/RbwG1x4c58tfl2MMu05jzP285Xf4dmh6sMdbEtD4vX/qRe6UvOcBUS1cW2YiOM7g7PYFBjB9JCLHZA7W6NzfVvoRZite58rRqmna+KojBtxzQG//wMz9qdvEq060Bfpha6XjOhYkONRyiEEL6rUqUKFy5c4LbbbuPTTz+lW7du7kUdZD4qhLiU3Wnni51fMGb1GP5L/g+AOmXrMP6W8dxxzR388ssvGo+wBDi2GeY8BknHwGCGLuOh5ePSCBBA7tgBDzJfA7VeTJJkvop8TJkyhZEjR/L0009z5swZKleuzJNPPsmoUaPc27zwwgukpaXRv39/EhMTadu2LUuWLCEiIufO4W+++YZBgwbRsWNH9Ho9PXv25P333/fbOAuab/rK4+pPVlYWY8aMYdmyZZjNZl544QW6d+/OjBkzePnllzEYDAwdOrRIgymOipr5mm5zFaBMBh0mg2cRvRI7kFe61bvYBn+KdXdxuv74nMwuvlYOYtcr5I4dCLHO1+wCa+7OV7UQm5ppy/c5gZScaXN33IZj52uaNY0BiwewZNfXzCOSLphd32h0P9wxGSwx2g5QCCGK6OWXX+aff/5h7dq1TJ48GaPRKPNRIcRlFEVh3l/zeHnFy/x17i8AqsVVY2z7sTzc+GGMeiM2W/DnmiWK0wkbp8DyceC0Q+mroddMqFS0FcNF4dTGL08W6g1U8TU5UzpfxeViY2N59913effdd6+4jU6nY9y4cYwbN+6K25QuXZpZs2YFYIQuY8aMoVevXiQkJPhtnx4XX0eNGsUnn3xCp06d2LBhA7169aJv375s2rSJyZMn06tXLwweZIqUNJYidqGqXZsRXhQO3SsWSuwAkKv4qmXna3ZB72T2YlsVg5j3CqHf+Zq7CzhWw85XdbGtUlGmoC/OVlR7z+7l3h/upfzZv9lJNJXRoxgj0XV9E5o+JN0FQohi4ciRI8yYMYNWrVqxZcsWmY8KIS6z4tAKXvrtJbac2AJAmcgyjGg3gqdbPk2EMbhz8BIr7Tz89BT886vrcYOecOe7st5AkKi1B086XwN112xO5qsUX0X4eeKJJwA4cOAA//77LzfddBORkZEoioLOx/Nqj6sLs2fP5ssvv+Suu+5iz549NGrUCLvdzq5du3x+8ZKgqJmv3i62BdL5eqlMmxo7EPximjvz9dLO14TgTvxi3JmvoV98Vbtgtch8PZ6d91o5zCIHvtz1JQMXDWCozc5oojEAlL0O3X1fQPm6Wg9PCCH85vvvv6d69er8+uuv7q/Z7XaaN2/Oli1b6N27t4ajE0JoaduJbQxfPpxlB5cBEG2KZljrYTzX+jniI+I1Hl0JcmQDzOkHKSfAGAG3TYTmfaQRIIjcsQMeZL6q9Qq/d75mx+5J56sIR+fPn+e+++5j5cqV6HQ6/vnnH66++mr69etHqVKlePvtt73ep2f3sQP//fefeyWxBg0aYLFYGDp0qBReC6Ee8Ira+epNXqm781WKr4DGna8ReTNfTya6iq8V44Jb3IsKo9gBtRCrReermvdaJUyKrxm2DB5f8DgvzOvDTzYYR4Sr8NrkIei/UgqvQohi59ixY5QuXZqjR48SHR2N2Wxm6NCh9O7dmyVLlmg9PCGEBvaf2899s++jxWctWHZwGSa9iWeuf4Z/B//LuA7jpPAaLE4nrHkLZt7pKryWqQ2PL4cWstBrsKm1B7MHsYWBuGvWane6m8gk81WEo6FDh2IymTh69ChRUVHur99///0+zzc9bgV0OByYzeacJxqNxMRIfmBh1IOZr5mv6kHLq9gB6XzNI93qKuJpseCW2vmqZt6cyI4dqBT0ztcQjR3IdH2+Y/OJHdCy8zUc8l73n9tPr9m9KH96L7uIpgJ6FFM0ujsnQ2Pp/BJCFE9Op5PRo0dTtWpVIGc+Wrt2bY4cOaLx6IQQwfRf8n+MWz2O6Tum41Ac6NDxUKOHGNt+LDVL1dR6eCVL6lmY+wQcXOl63Kg33PG2rDegEbUOYPGghuCOHbD5r0lHPffV6XLO7YQIJ7/++itLly51zzdVRZlvevyboCgKffr0ca/wlZmZyVNPPUV0dHSe7ebOnevTQIortfPV10Johg9dm+7iq2S+Ar5FN/iLmnGjZr6eyo4dqBTkzNeo7NgBLbpJC5J/56vJ/b2iZKr44r8w6Xz9dve3DFjYn+esNl4m2nULQ/n66HrNhHLXajw6IYQIrLFjxzJlyhQyMjLQ6XQ89dRTWK1WrFYrPXr0AGQ+KkRxdiHjAhPXTWTK5ilk2l1z627XduP1W16nYYWGGo+uBDq0Bn58HFJPgzES7ngLmjwo3a4a8inz1Y+1AzXvNcZiRK+Xz4EIP2lpaXk6XlUXLlxw10S95XHx9dFHH83z+KGHHvLpBUsaTTJfJXYgDy1jB3K6OPNmvlaKD25xT11wS+0CDhU5ma85t6OohViHUyHT5gzq+6YuuFU1RDtfM+2ZDF0ylAVbP2E+kdxM9oG/eR9XnpYpNMcthBD+UqVKFS5evEjNmjXR6XTcfffdxMTEsHr1aipXrkx8vNxeLERxlWZN473f32PS+kkkZSUB0LZ6WyZ2nEib6m00Hl0J5HTAmjdh9RugOKFcHeg1U2KvQoA789WD4qslAHfNJmcXXyXvVYSrdu3a8eWXX/Lqq68CoNPpcDqdTJo0iQ4dOvi0T4+LrzNmzPDpBUo6i7uNP4iZrwFasTBc+fJv6C9qxk1yhp2UTJu72Bjsztec2IHQz3yNMhnQ6UBRICXLFtTiaygvuPXvhX9dMQMn/2An0ZRDj2KORtftfWh4r9bDE0KIoFiyZAkdO3bk1KlT6PV6dDodmzdvJiMjg/Xr13PNNddoPUQhhJ9ZHVY+3/4541aP43TaaQAaVWjEhI4TuL3W7bIGiRZSTrliBg6tcT1u+hDc/iaYL+8UE8Gn1h7URrCCBKJ2oHa+St6rCFeTJk2iY8eObN26FavVygsvvMCff/7JhQsXWL9+vU/7lACOAHMXX7XIfJXYASDn31BddCqYcne+ql2vcRFGdydqsKiF55DLfM0eT+7MV71eR4zZSEqWndRMO+VjgzOWLLuDMylZQOjFDvy490f6z3+M57OyeInsqJeKDdH1+gLKSKFBCFFyNGjQgL///psPPviA2NhYUlNT6dGjBwMHDqRSpUpaD08I4UdOxcl3e75j5MqRHLx4EICrS13Nqx1epXeD3uh1Hq8dLfzp3xUwtz+knQVTNMh6AyHHHTtg8jx2wK+dr9mRe9L5KsJVIOabUnwNMLMWsQPZB1CbdL4CObfaa5n5mmV3cuR8OhD8yAEI4QW33LEDeQ9FsRHZxdcgjvdkoqs4HmHSUzraXMjWwWF1WHn+1+eZ9/sUFhBJGzVmoOUT0Pk1MAW3g1oIIbRks9m47bbbmDp1Ki+//LLWwxFCBIiiKPxy4BdGLB/BrtO7AKgQXYGRN43kieZPYDaExjytxHHYYdUEWPs2oECFBnDvDFlvIASpjV9qHGFB1O5YfxZf3Z2vkVJuEuEnUPNN+W0IsKJmqGT6EjtgkM7X3LTMfM1dVPz7dAoAlRKCXzBTu37TrA6cTiVkgs9TM13vzaWdwDERRkiC1MzgFV+P51psKxRuXzuceJj759xP+f+2s4NoyqBHscSiu+sDqN9d6+EJIUTQmUwm/vjjD62HIYQIoA3HNjB8+XDWHHHdzh5nieOFG19gSKshRJujC3m2CJjkEzCnHxzd4HrcvC/cNkHWGwhRau0hwovOV1/v1M1PssQOiDAWqPmm3KsRYGqrv68HM7VwGOFF4TAQodnhTMvMV4Ne576lfv+p7OJrkPNeIW8RWO2mDgVqJ25sxCXF1+zxpgSx81XNe61SSvusqgX7F3D91Cbc998uFhJFGfRQuSm6J9dK4VUIUaI99NBDTJs2TethCCH8bM+ZPdz93d20md6GNUfWYDFY+F/r/3Fw8EFevullKbxq6Z9lMLWtq/BqjoWe06Dbu1J4DWHu2AEPMl8tAVisWxbcEuEuEPNN6XwNMIuGsQNSfHXx5d/Qn9Rb6N2drxrEDkSY9Oh14FRcBc9gZ85eyZViB2Kyr5KmaNL5qt2t/DaHjRHLRzBnw9ssJIob1JiBVk9DpzFgtGg2NiGECAV2u53p06fz22+/0bx5c6Kj8xZkJk+erNHIhBC+OJx4mNGrRvPVrq9QUNDr9DzW5DFG3TyKavHVtB5eyeawwYpXYf17rscVG0GvmbLeQBjIKb56EDtg8v9ds8mZauyAFF9FeArEfNOjCsyCBQs83uFdd93l9SCKM3cbv02D4qvEDgA53cNaLLgFrj86J5Iy+fdsKgAVNeh81el0RGcvYpVmDY3OV6eCeywxl3S+qt3Cqdl/uIMhd+yAFo4lHaP3j70pf3QzO4ghAR1KRDy67h9DnTs0GZMQQoSSBQsWsGrVKqpXr05WVhYbNmzI832dTuees8p8VIjQdibtDK+veZ2Pt36Mzema7/Ws25PXbnmNOmXraDw6QeIxmPMY/LfZ9fj6/nDrq7LeQBiwO5w4nArgWeerOQCdr0nS+SrC3J49e2jWrBkAf//9d57v+RpR6FE1qnv37h7tTKfT4XCERmEnVFiKWAjNtHl/y7zJoEYdSPEVcmIHIs3apGyot9TbHK4/gpU16HwFV65qSpY9ZBbdysp1qLis81UtvmoSOxD892fJgSU89uODvJSRxmCyYw+qtkR373RIqB708QghRCjyZD7avXt3mY8KEcKSs5KZvHEyb298m1SrqzGhY82OTOg4gZZVWmo8OgHAXz/DTwMgMxEs8XD3FKh3t9ajEh7KXQMwe9D5mpP56s/YAdc5nCy4JcLVypUr/b5Pj34bnE4p4vnKUsQAa3fmqzedrwG4ehXO0q2ug3+kSaPO10uCxrVYcAsg2uL6DAWzoFkQtfhqMuguuyVG7YQNauaru/M1eJmvdqed0StH8/3aCSwkiuZqzMCNg6HjKDDI1WIhhFDJfFSI8JVpz2Tq1qm8vvZ1zqWfA6B5peZM7DSRTld30nh0AgC7FX4bA5s+dD2u3AzunQ6la2o6LOEdb4uvanesXzNfM6XzVYhLyaWIAHNnvvoaO+Du2pTMV19pueAWXL6YlBYLbgHunFe1GK21zOzia4zFeFnrvvpvlhqkzFenU+FkUnA7X0+knOCBHx+g/OH1bCeGOHQokaXR3TMVru0SlDEIIYQQQgSSw+ngqz++YvSq0RxNOgrAtWWu5fVbXqdn3Z4+374p/OziYVfMwPFtrsetnoZOY8Fo1nRYwntqDcBk0GHQF/77FYjagRo7cGkTkhAlmU/F17S0NFavXs3Ro0exWq15vjd48GC/DKy4KGobf6ZkvhZZhg/RDf6UO2g8PtKkWfZstFm9lT80bsV0F18jLv/3CHbswNnULGwOBYNeR4XYwC9qtfzgch778f94KS2FAWrMQPXW6HpOg/gqAX99IYQoDmQ+KkToUhSF+fvn8/KKl9l7di8AVWKrMKb9GPo06YNRLz1AIWPvApg/CLKSICIBun8MdbpqPSrhI/WOW0/yXiFQsQPS+SrEpbz+q7djxw66du1Keno6aWlplC5dmnPnzhEVFUX58uVlsnsJSxGvJKX70Pla1Ncsbnz5N/Sn3J2vWnW9Qk7sQKhkvmY6XFdiYyyX/1EOdufrf9l5rxXjIjAaApcN7HA6eG3Na3y7ahwLiKQx2d0EbYdBh5fBICciQgjhCZmPChG6Vh9ezUvLX2LTf5sAKBVRihHtRjCw5UAiTdqsfSDyYc+CX1+BzZ+6Hldt6YoZkPUGwppaRL001u1KzH5eL0ZRFJIz1cxXKb4KofK6yjB06FC6devGxYsXiYyMZNOmTRw5coTmzZvz1ltvBWKMYc1iysl8VRTF6+dn+NL5avB/bku4cjgV9x8Sb/4N/Sn37RbaFl9dhb3QKb66/jfWkl/nq+vfLCVIxdecvNfAnRCcTj3Nbd/cxt+rXmMr0TTGgBJVBh76ETqNlsKrEEJcQbNmzbh48SIA48aNIz09XeajQoSgHSd3cPs3t9P+i/Zs+m8TUaYoRrQdwcFnD/K/G/8nhddQcv5fmHZrTuG1zbPQ9xcpvBYDatyhp8VXtV5h9XGNmkulWR04nK66h3S+inCS33zTn7wuvu7cuZPnnnsOvV6PwWAgKyuLatWqMWnSJEaMGOHXwRUHaru/UwG70/viqzt2wJfMV4kdcBevAc1u94/NVXytGK/dpDOn+BoGsQNBXnDr+MXA5r2uObKGG6c24f5/1/ENUcSggxrt0D21HmrJIhNCCFGQffv2kZaWBsDYsWNJTU2V+agQIeTAhQP834//R7NPm7HkwBKMeiNPt3iaA88c4PWOr5MQkaD1EEVue+bCJzfDyV0QWRoemA23jpOFXosJNXbAk8W2wP+dr2req9mg97gALEQoyG++6U9eV6NMJhN6veuXqHz58hw9epS6desSHx/PsWPH/Dq44iD3ASfL7sTk5S3N7gW3fMh8tUnnq3txKZ0OIkzaHPzjInN+zSpr2fmaXcAPxQW3LpWT+WoLyliOJ7quavm789WpOHlj3Rt8s2Ik85UIGmBGQYfu5hfg5hdBr003thBChJMmTZrQt29f2rZti6IovPXWW9hsNj766CPKlCmD0WhkwoQJ1KpVi/vuu0/mo0IEyYmUE7y6+lU+3/E5dqdrfvlAwwcY134c15S+RuPRicvYMmDJcNg2w/W4emuQ9QaKnZzYAc/OMyy5GrcURSnyInhq3mtcpEkW1BNhJb/5ZkxMTL7bjho1yuv9e118bdq0KVu2bKF27drcfPPNjBo1inPnzvHVV1/RoEEDrwdQ3JlzFVutdid4sZaPoiikF6HzNUs6X8m05kQOaHXwz9v5qn3sQLAWsSqMmiiQX+drsDNfTyRmAv7tfD2Xfo5H5j1C+X9+43eiiEaHM7oc+p7T4Oqb/fY6QghR3M2cOZPRo0ezaNEidDodv/zyCwaDgfnz51OqVCkUReHHH3+kXLlybNiwQeajQgRYYmYib6x7g/d+f48Mu+vuoa61u/L6La/TpGITbQcn8nfuH5jdB07vAXTQ7jloP1xir4ohNXrQ4mHjkVqkVbLv1DUZinbOnOQuvspnS4SX/OabRuPln2OdThec4uv48eNJSUkB4PXXX+eRRx5hwIAB1K5dm+nTp3s9gOJOr9dhNuixOpzuWwA8lWV3osbEepf5mrPglj+uXoWzdJureBel0WJbAHG5iouVA5gpWpiYkMt8dX0u8898zSkUB+MzrMYO+Ov92XBsA31n38eI5PM8imufytXt0ff4DGLK++U1hBCipLjuuuv47rvvANDr9SxfvpyjR4+SkpJChw4dOHPmDI888ggbNmzg7NmzMh8VIkDSbel8sPkDJq6byMVMVy7ejdVuZELHCdx01U0aj05c0a7vYdFQsKVBVFno+Rlcc4vWoxIBotYcPF5wq4h36l5K7XyVvFcRbvKbb5Yv779zd6+Lry1atHD///Lly7NkyRK/Daa4shizi6827zpRM3PllUb4EDsAYHMomI3hU3w9fC6Nv04lF7iN3e5g13kdhj9PYyzkdopD51y3k3vz7+dvodL5qmbepllDLPM1n+Kr2vlqc7gWTAvk+6coit8W3FIUhckbJ/P1b8P5yWmmLmYUnR5dhxHo2g6TmAEhhCgip9M1l8o9GZb5qBCBZXPYmLFzBmNXj+VEygkA6perz/iO4+l2bbcS3egR0qzp8MvzsONr1+Ma7aDn5xBbUdtxiYDyNnYgd+3A2zt18+PufI2Q4qsIX+p805+kFzwIzEY9ZHkfYq0uFmUy6Ly6ApX7KpfV4fQ4bFtrmTYH3aas83CRJQPT/97l8b7zK/AFS0JUzh+eShoWX9Xb+5PSg5OjWpiCFtyKzrU4WmqWPaDF1+QMuzuKoSjF14sZF+nz06OU27+EDUQQiQ5nTAX0986AGm38NVwhhCjx/v33X95991327dsHQL169Xj22We55hrJmBTCn5yKkzl75/DKilf458I/AFwVfxXjOozjwYYPYpCLyqHrzF+umIGz+wCda62Bm1+QRoASQG348rTz1aDXYdTrsDsVd2RBUSRnx8ZJ56sId/6eb3pdkapZs2aBVzcPHjzo00CKM3eItZcHs3QfFtsC8hRq/XH1KljOpmSRkmVHr4Nm1UtdcTtFUbhw8SKlS5Xy6Eq7XqfjkRuv8udQvVI2xsKA9tcQYzG6u0+1ULu8Kyz6zxNJ2B1OjEW8paSoCup81et1xFiMpGbZSc20UzYmcB/i/7IX2yoTbfYqWzm3Lce30Hd2L0YknuEBNWagVif093wC0WX9NlYhhCjpli5dyl133QVARITrgua6deuYMmUKFStWJDLSdQyW+agQvlMUhWUHlzF8+XC2n9wOQLmocrxy0ys82fxJLMYwObkoqXZ8A4ufA3sGxFSAHp/JegMliBo74E0Dltmox251eB2TmB/JfBXFgTrfbNKkCW3auBqp1q9fT/369Vm4cCG33nqr1/v0+jdiyJAheR7bbDZ27NjBkiVLeP75570eQElgyS6eenswy7B6v9gWuK5eGfQ6HH66ehUsKdlXyUpHW5gz4MYrbmez2fj555/p2vV6TKbwuKL24m11tB4C11aIJTbCSEqmnb9OpdCgSrym43FnvubT+Qq4i68pAV50S8179WWxLUVR+GDzB3y19H/Mc5qojckVM9BxFLobnwV9eHSdCyFEuHjppZcYOnQolSpVyvP1n376iV27dmG1WmU+KkQRbD6+mZd+e4mVh1cCEGOO4fkbn2doq6HEWmI1Hp0oUFYq/Pw/2PWt6/HVHaDHp7LeQAmTEzvgXfE13erwT+erZL6KYkCdb06cOPGyr7/44ovBKb4+++yz+X79ww8/ZOvWrV4PoCRQD3zexg6oma/edr6Ca9GtDKd/DqDBkpKp5sPIVbJAMOh1NL+qFKv2n2XL4QshUHx1/W+MJf8/zDERRkiGlKzAxiScyM57rRzvXfE1KTOJxxf0o9zeBawhggh0OOMqo793JlS/IQAjFUIIsW/fPn744Qdq166d5+u33347jRo14u2335b5qBA+2Hd2H6+sfIW5++YCYDaYGdhyIMPbDqdcdDmNRycKdfpPV8zAub9Bp4cOI6Dtc9IIUAJ5m/nq2ta3ekV+kiXzVRQD6nzzUo899hjvvvuuT/v029H49ttv58cff/TX7oqVnIOZl52v2cVXX/Iu1dsMrI7QWFzJE2ruZn4ZoMI/WtYoDcDWwxc1HglkFZD5CjlxBKmB7nxN9L7zdcfJHdw8tSn37f2Zj4gkAh3Ktbehf2q9FF6FECKAypUrx86dOy/7+s6dOylfvrzMR4Xw0rGkY/Sb348GHzdg7r656HV6+jTpw9+D/mZyl8lSeA11igLbZsJnt7gKr7GVoc9iuOl5KbyWUO7iq8m7zldwrRdTVMmZ0vkqwl9h801f+K3KNWfOHEqXLu2v3RUr6sFMDb/2lJr5GuVDDqXZj1evgkW9vfxKt6GLolOLr1sOX0BRFE1Xp1VrqldaDE39HKR6tACb79zFVw8W21IUhU+3fcoXvwzhR4eRazDh1BnQ3zoOXeuBIKv9CiFEQD3xxBP079+fgwcPcuONroii9evX88YbbzBs2DCZjwrhoXPp55iwdgIfbvmQLEcWAN3rdOe1Dq9Rv3x9jUcnPJKZDIuGwJ7sC061boV7PoHoMpoOS2hLbfjyKnbA4Fu9Ij85ma9SfBXhq7D5pi+8rnI1bdo0T8FGURROnTrF2bNn+eijj3waRHGntvx7eyXJHTvgS/HV4NsiX1pSYwdir3Abuii6RlXjMRv0nEnJ4uiFdK4qE63JOBRFcccOXKnYHrTiq4eZr6nWVJ5c2J+yu39kFRbM6HDEVcFw35dQtUVAxyiEEMJl5MiRxMbG8uKLL2KzueYNJpOJ8uXL89FHH8l8VIhCpFpTeWfjO7y54U1SrCkA3HzVzUzsNJFWVVtpPDrhsZO7XDEDFw6CzgCdRkPrZ6TbVbgLqN7EDph9rFfkJznDde4mna8inKnzzbfffpvhw4cDULlyZcaMGcPgwYN92qfXxde77747T/FVr9dTrlw52rdvT5062i8qFIosPna+uhfc8iF2QH1Nm0Px+rlaSZbO14CLMBloWDWebUcusuXwRc2Kr5k2J05cx5HoK3S+qh2xAV9wy4PO192nd9Pv+54Mv/Af9+BaXVupcyeGuz+AyFIBHZ8QQogcOp2OoUOHkpSUhNVqBcBisch8VIhCWB1WPtn6Ca+tfY0zaWcAaFqxKRM6TqDzNZ01vRtKeEFRYMvnsHQEOKwQVxV6zYBq12s9MhEi1DtfzV50vqq1A380biVJ5qsoBtT55tChQ0lJcV2ojI0t2qKTXle5xowZU6QXLInUvBVvM1/V2IFIs/fFSLMfD6DBIpmvwdGyRmm2HbnI1sMXuLd5VU3GoL7XOh1EXeHigroQVyA7XzNtDs6luk7eq16h83XGjhnMXDSIHxx6amDCqTei7zIB3fVPSMyAEEJoROajQnjG4XTw7Z5vGblyJIcTDwNQq3QtXuvwGr3q90Kvk07JsJGZBAuegb3zXY+v6wp3fwhRErUicljdC255n/nqbb0iP5L5KoqbohZdVV5XuQwGAydPnrwsZPb8+fOUL18eRxgt8BQs7gwVLwuh6oJbkV6EZbtfMwwX3HLHDshVsoBqWaMUU1e7cl+1ohZUo81G9Pr8C5hqET6QC26dyO56jTIbLpsgpNvSGbT4aUrt/JbfsGBChyOhuitmoHLTgI1JCCFE4WQ+KkTBFEVh8T+LGbF8BLvP7AagUkwlRt88mseaPobJIPPtsHJ8G8zuC4lHQG+CW8dCq6elEUBcxpfMV391vtocTncDWVykNFQJkZvXvxGKkv9t7FlZWZjN5iIPqDhS81a8Lb66M199iB0Iz8xXV5EtTjpfA6r5Va7b5P89m8b51CzKxFiCPgZ3l7Plyp/tWHfsgC1g48gdOZD7drt9Z/fx+Pc9GH7uCHeqMQP178HQ7T2IiA/YeIQQQnhG5qNCXNnaI2sZvnw464+tByAhIoEX27zI4BsGE2WK0nh0wiuKAr9PhV9HgtMGCdXh3plQtbnWIxMhSq05WLyoIfir+JqckXPeJg1VQuTlcZXr/fffB1zZB59//jkxMTHu7zkcDtasWSMZW1eQEzvgW+ZrhC8Lbhl9e00tpUjma1AkRJm5tkIMf59OZeuRi3SpXzHoY0jLcn22Y66Q9wq5Ol8DGDuQ32Jb3/zxDTMXPMl3dh3VMOHUm9Df/ga6Fo9Jd4EQQmhM5qNCXNmuU7sYsWIEP//zMwCRxkieveFZXmjzAqUkoz78pF+A+YNg/2LX47rd4K4PIDJB02GJ0JZVpNiBotUO1LzXWIsRwxXubhSipPK4yvXOO+8Ark6DqVOnYjDkFATNZjM1atRg6tSp/h9hMWDxMUMlPbvzNcrkfTHSFIadr+rt5WrWpwicFjVKu4qvhy9oUnz1JN83GAtu5e58zbBlMPSXZym1/Qt+wYIRHfZSNTHe/xVUbBiwMQghhPCMzWbjxRdfpGzZsjIfFSKXgxcPMnLlSL7d/S0KCgadgcebPc6om0dRObay1sMTvji2Beb0haRjYDBD59dB1hsQHsiyqbEDnjdw+euuWXUB7TjJexVhzGazcdtttzF16lRq167tt/16XNU7dOgQAB06dGDu3LmUKiVXTz3lvpJk8zJ2wL3gVlEyX8On+JrsznyVztdAu75GaWb9fpTNhy9q8vo5sQMad75mF18jLOl0/fR6Xjx7kNuyYwacDXthvPMdsPgnYFsIIUTRmEwmYmJiWLFiBf3795f5qCjxTqWe4rU1r/HJtk+wO13zpfvr38+rHV6ldhn/nTCKIHI6YeMHsHwsOO1Qqib0mgmVm2g9MhEm1O5Vs1eZr65CbVFrB2rnqxRfRTgzmUz88ccfft+v11WulStX+n0QxZ2vB7OMomS++im3JZgkdiB4WtRwnaz+eTyJdKudKHNw/809Kb7GBTF2YMvmIXzDYSpjxGEwY7jjbfRNH5buAiGECDEPPfQQ06ZNk/moKNGSMpN4c8ObvLPpHdJt6QB0uaYL4zuOp1mlZhqPTvgs7Tz8NAD+Wep6XL8HdHsPIuK0HZcIK9aixA7YirZYpZr5Gi+LbYkwp843J06c6Ld9ev1b0bNnT66//npefPHFPF+fNGkSW7ZsYfbs2X4bXHFh8bHzVS2+RvhQfLWEYexAirvzVa6UBVqVhEgqxUdwMimTnccSufGaskF9/ZyIiYJiB0x5tvW3LHsWe04cZbDhV55V9mLQ6bGVvgbT/V9DhXoBeU0hhBBFY7fbmT59Op988gnXXnstbdq0yfP9ihUrynxUFFsZtgw+3PIhE9ZN4ELGBQBuqHIDEzpOoEPNDhqPThTJkY3wYz9IPg4GC9z+BjTvI40Awmtq1KFPxVd/db7K+bwIc+p887fffqN58+ZER0fn+f7kyZO93qfXxdc1a9YwZsyYy75+++238/bbb3s9gJLA58zX7NgBX7oSw63zVVEUd4ejdL4Gnk6no0WN0izcdYKthy8Gv/jqXnDryhcW1NiBlAB0vh66eIinvuvJJ04LbU17AXA2/j9Md7wN5uhCni2EEEIre/bsoVmzZqxfvx6n08mOHTvc39PpdLz33nsyHxXFjt1pZ+bOmYxZNYbjKccBqFu2LuM7jufu6+5GJwW68OV0wvp3YMXroDigTC3o9QVUbKD1yESYci+45UUDl8VPtQM1RjBeYgdEmFPnmwB///13nu/5+jfX6ypXamoqZrP5sq+bTCaSk5N9GkRxZ86OHfB29cBMW8nJfE23OnAqrv8vxdfguL5GKRbuOsGWwxeC/toeZb5mf89qd5Jld3gVGl+Q+X/NZ/rcR/kiS6GiAdIVCxHd30Xf9AG/7F8IIUTgqHEDkZGRfP3111x33XV5vv/XX3/JfFQUG4qiMHffXF5e8TL7z+8HoFpcNcZ1GMfDjR7GoPfP3EhoJPUszOsP/65wPW50P9wxGSwx2o5LhLWsIsQOFLX4KpmvorgIRLyV11W9hg0b8v3331/29e+++4569eRW3fz4eiUpw+p77IB7xcIwKb6qea8Gvc6njFvhvRY1SgOw/chF7EH+nLiLrwUU2nMXZv0RPWBz2Hh+yVB2fXc/86xOKurgL2c1+ke+KYVXIYQIM9deey2vv/46GRmu7G5FcV3BlfmoKC6WH1zO9Z9fz72z72X/+f2UiSzD5M6T+fuZv+nTpI8UXsPdobUwta2r8GqMhLs+gHs+kcKrKDI1t9WbBbfcsQNF7XzNcJ2zSeerKC4OHDjA0qVLL5tv+sLrFsORI0fSo0cP/v33X2655RYAli9fzrfffiv5WldgMfkWO1CSFtzKyXs1yq1TQXJthVhiI4ykZNr561QKDarEB+21Pel8Neh1RJkNpFsdpGbZKRNj8fn1jiYdZeD3PfjfiX3cjGs/h67qyd37u9GkSkWf9yuEECK4zp8/z3333ccff/zBH3/8QWpqKnfffTeff/4558+f559//pH5qAhrW09sZfjy4fx28DcAok3RPNf6OZ678TniLLLwUthzOmDNW7B6IihOKFcHes2E8nW1HpkoJnzqfPXTejHJ7sxXuZNVhDd1vrly5Up0Oh3//PMPV199Nf369aNUqVI+RVx5/VvRrVs3fvrpJ8aPH8+cOXOIjIykUaNG/Pbbb9x8881eD6AksPgYO5BRgjJfUzwoxgn/Muh1NL+qFKv2n2XL4QshV3xVv58eE3xuAACiFUlEQVRudbg7o33x8z8/M2POg0zPslMOIzZjBKa7P2RVcnOy9u+lXKzvRV0hhBDBNXToUEwmE8eOHaN27docOXKEp59+GqPRiN1ul/moCFv7z+1n5MqRzN7runhg0psY0GIAL9/0MuWjy2s8OuEXKadh7uNwaI3rcZOHoOskWW9A+I2iKO47X72JbFPzYf2W+Rolna8ivKnzzaNHj1K3bs7Fsfvvv59hw4b5VHz1PkwUuOOOO1i/fj1paWmcO3eOFStWcPPNN7Nnzx5fdlfsudv4bV4WX0tU56u62JYcqIOpZXb0QLBzX3OKrwV/ttX831QfFt2yO+28/OsL7PqmB7OznJRDT1a56zA9tR4a3ktiugTCCyFKluPHj/PQQw9RpkwZIiMjadiwIVu3bnV/X1EURo0aRaVKlYiMjKRTp078888/efZx4cIFHnzwQeLi4khISKBfv36kpqbm2eaPP/6gXbt2REREUK1aNSZNmuS3n+HXX3/ljTfeoGrVqhiNRmbPnk1aWho7duxAp9PJfFSEnf+S/6P/wv7U/6g+s/fORoeORxo/wt/P/M17t78nhdfi4t+VMLWNq/BqinZFDHT/UAqvwq9sDgX1rmj17ltPWAy+3al7KXfmq5zTizCXe76Zm3rh3xc+FV9zS0lJ4dNPP+X666+ncePGRd1dsWTxYfErRVHcxdcIXxbcCrvM15zYARE8OcXXi0XKL/FWaqbrs11o52v2H25vM1+PJx+n97S2dN3wIcOzYwYczfti6b8GytYCciYHUnwVQpQEFy9epE2bNphMJn755Rf27t3L22+/TalSpdzbTJo0iffff5+pU6fy+++/Ex0dTZcuXcjMzHRv8+CDD/Lnn3+ybNkyFi1axJo1a+jfv7/7+8nJyXTu3JmrrrqKbdu28eabbzJmzBg+/fRTv/wcaWlpREVFXfb1Y8eOoSiKzEdF2LiQcYEXlr1A7Sm1+Wz7ZzgUB3dddxd/DPiDL7p/QY2EGloPUfiDww4rXoOv7oG0s1C+PvRfBY17az0yUQzlLp76tOBWEWsHyXJ+JYqJK803L1y4gMXi252zPhdf16xZwyOPPEKlSpV46623uOWWW9i0aZOvuyvWLEbvryRl2Z3uq1a+dL76usiXVtTOV8mHCa5GVeMxG/ScTcni6IX0oL2up7EDsRbvO19//fdXXviwEZ8c/5M2GLEZI6HXTAzd3gVThHs7tfiaILfFCCHCWEpKCsnJye7/srKy8t3ujTfeoFq1asyYMYPrr7+emjVr0rlzZ6655hrAddH33Xff5ZVXXuHuu++mUaNGfPnll5w4cYKffvoJgH379rFkyRI+//xzbrjhBtq2bcuUKVP47rvvOHHiBADffPMNVquV6dOnU79+fXr37s3gwYOZPHmyX37edu3a8eWXX7ofb9myhYcffpiOHTui1+tlPipCXpo1jfFrx3P1e1fz5oY3ybRn0rZ6W9b1Xcf83vNpUL6B1kMU/pJ8Ar68C9a8CSjQvA88sRzKXav1yEQxlTvmUG3G8oS/agfuzlcpvoowd+l8U6fT4XQ6mTRpEh06dPBpn15Vuk6dOsXMmTOZNm0aycnJ3HfffWRlZfHTTz/JyrIFcGe+ehE7oOa9gm/FV5OfQrODRe1slMzX4IowGWhYNZ5tRy6y5fBFrioTnFuf3MXXQort6uchxYPiq8Pp4PWVo4lZ+zbfYAb0ZJavS0TvWVD66su2l85XIURxcOn8a/To0YwZM+ay7RYsWECXLl3o1asXq1evpkqVKjz99NM88cQTABw6dIhTp07RqVMn93Pi4+O54YYb2LhxI71792bjxo0kJCTQokUL9zadOnVCr9fz+++/c88997Bx40ZuuukmzGaze5suXbrwxhtvcPHixTydtr6YNGkS7du354cffiA1NZVHH32UqKgoHA4Hs2fP5rbbbivS/oUIFKvDyufbP2fc6nGcTjsNQKMKjZjQcQK317pdFpwtbv75Deb1h/TzYI6Bbu9Bw3u1HpUo5tTiq9mo9+qY4o5JLELtQFEUkrPP6eX8SoS7SZMm0bFjR7Zu3YrVauWFF17gzz//5MKFC6xfv96nfXp8OaRbt25cd911/PHHH7z77rucOHGCKVOm+PSiJY2at+LNwUyNHDAb9Bi9uGql8tetA8GSEzsgB+pgc0cPHApO7qvV7nT/LhQeO5BdfM3+fFzJqdRTPDzjZjqvfYdhuE747S2fIKL/6nwLrwCJ6VYA4iPN+X5fCCHCwd69e0lKSnL/N3z48Hy3O3jwIB9//DG1a9dm6dKlDBgwgMGDB/PFF18ArgvsABUqVMjzvAoVKri/d+rUKcqXz5s/aTQaKV26dJ5t8ttH7tcoiuHDh2Oz2YiIiKBt27Z06NDBveBW9erVi7x/IfzNqTiZtXsWdT+sy8CfB3I67TRXl7qab3p8w44nd9C1dlcpvBYnDhssGw3f9HQVXis2hCfXSOFVBEVWdg3Bm8gB8M96MWlWBw6n69ZdyXwVBQnWGgRF0aBBA/7++2/atm3L3XffTVpaGj169GDHjh3uu8a85XGb4S+//MLgwYMZMGAAtWvX9unFSiqzDwHW7rxXL4Ky87ymH65eBVOye8Et6XwNtpY1SjF1NWw5Epzia1quLtZoc8Fd3WpxtqDM15WHVvLl9/fxYWYWpTCSZYrE0uNzjHXvLHDf0vkqhCgOYmNjiYuLK3Q7p9NJixYtGD9+PABNmzZlz549TJ06lUcffTTQw/SbK81H33jjDQ1HJcTlFEVhyYElDF8+nF2ndwFQIboCo24exePNHsdskIu/xU7SfzDnMTj2u+txyyeg82t5Yq+ECCS18Uq989ZT6vZFKb6qea9mg97nGoYo/tQ1CDp06MAvv/xCuXLl+Oeff/Jdg+CLL76gZs2ajBw5ki5durB3714iIlzH0wcffJCTJ0+ybNkybDYbffv2pX///syaNctvY42Pj+fll1/22/48rnStW7eOadOm0bx5c+rWrcvDDz9M794SFO4JtfPVaneiKIpHV7fV2IEos2/FSHOYxQ6kuIuvUggLtuZXuQ50B8+mcT41izIxvgVIe0qNHDDrlUK7utVifH6Zr07FyRurxxG96g1mYAZ0ZFSoT2Tvb6HUVYWOQzJfhRAlSaVKlS6LKKhbty4//vgjABUrVgTg9OnTVKpUyb3N6dOnadKkiXubM2fO5NmH3W7nwoUL7udXrFiR06dP59lGfaxuUxTr1q3jo48+omHDhsTGxlKrVi1uv/32Iu9XCH/aeGwjLy1/iTVH1gAQZ4njhRtfYEirIUTL6vbF0/5f4KcBkHERLHFw1xSo313rUYkSRo059LXztSiNWzl5r0bp5hdXlHsNAlXNmjXd///SNQgAvvzySypUqMBPP/1E79693WsQbNmyxR2FNWXKFLp27cpbb71F5cqV/TLWixcvMm3aNPbt2we4or769u1L6dKlfdqfx7+VrVq14rPPPuPkyZM8+eSTfPfdd1SuXBmn08myZctISUnxaQAlgXolyamA3enZivJq52tkIZ2BV+KPWweCKTXLdbAuLANU+F9ClJlrK8QAsPXIxYC/nlpoj/Dgo32lztezaWfpN/MWbl31FoOzYwZsNzxJ5BOrPCq8Kooina9CiBKlTZs27N+/P8/X/v77b666ynXMrFmzJhUrVmT58uXu7ycnJ/P777/TunVrAFq3bk1iYiLbtm1zb7NixQqcTic33HCDe5s1a9Zgs+XExSxbtozrrruuyHmvAFarlfnz51O2bFmqVavG33//zejRo7Hb7UydOlXmo0JTe87s4e7v7ubG6Tey5sgaLAYL/2v9Pw4OPsjLN70shdfiyG6FpS/Dt71dhdfKTV0xA1J4FRpQi6cWLztPc+7ULXrnqyy2VTJ5ugDsggULaNGiBb169aJ8+fI0bdqUzz77zP39wtYgAApdg8Af1qxZQ40aNXj//fe5ePEiFy9e5P3336dmzZqsWbPGp3163Q8eHR3NY489xrp169i9ezfPPfccEydOpHz58tx1110+DaK4y33lydMDmtr5GuHDYlsQjpmvruJanBRfNRHM3Fe1i9XiwUdb7YTOveDWuqPreOWDBrx7ZDstMJBpioL/+x7T7ZPA6NktfOlWBzaH60KIdL4KIUqCoUOHsmnTJsaPH8+BAweYNWsWn376KQMHDgRcq7gOGTKE1157jQULFrB7924eeeQRKleuTPfu3QFXp+xtt93GE088webNm1m/fj2DBg2id+/e7i6DBx54ALPZTL9+/fjzzz/5/vvvee+99xg2bJhffo6BAwdy//33c+TIEbZv38758+f5888/adSoER9//LHMR4UmDiceps9PfWj0cSMW7F+AXqenX9N+HBh8gDc7v0mZqDJaD1EEwsXDMOM22PiB63Grp+GxX6F0zQKfJkSgqDGHXscOuO/U9Twm8VLuzle5k7VEqlevHvHx8e7/JkyYkO92wVqDoKjU+eahQ4eYO3cuc+fO5eDBg/Tu3ds9d/ZWkSpd1113HZMmTWLChAksXLiQ6dOnF2V3xZY5163VWTZHoYsMQa7OVx/zUtSCry3Miq+S+aqNljVK883vR9kShM5XtcvZo87XiJzOV6fi5J21E4la8RqfYAJ0pFVsSPT/fQfxVb0agzo5MBl0RPp4gUMIIcJJy5YtmTdvHsOHD2fcuHHUrFmTd999lwcffNC9zQsvvEBaWhr9+/cnMTGRtm3bsmTJEne+FsA333zDoEGD6NixI3q9np49e/L++++7vx8fH8+vv/7KwIEDad68OWXLlmXUqFH079/fLz/HgQMHmDNnDgZDzrG7Xr16/PDDDzRu3Jhvv/1W5qMiaBJtiTy37Dk+2f4JVodrIc+edXvy2i2vUadsHY1HJwJq30L4aSBkJUFEPHT/GOrcofWoRAmnxg6YvY0dMBS9cUtdw0U6X0umvXv3UqVKFfdjiyX/KMNwWYMgv/mmwWBg2LBhfPnllz7t0y+VLoPBQPfu3d2dESIvvV6H2aDH6nB6fEAreuZr0UOzg0ldzV4yX7XRoobrVtA/jyeRbrX7/LnzRE7sQOERHLHZFyoSMzIZ8OWtDDj0O01wfUayWg8iutNYMHg/1tyRA5JJJIQoKe68807uvPPKixHqdDrGjRvHuHHjrrhN6dKlC13MoFGjRqxdu9bncRakWbNm7Nu3j+uuuy7P1/ft20eTJk1kPiqCIjkrmTfXvclb+94i05kJQMeaHZnQcQItq7TUeHQioOxZ8OtI2PyJ63HVlnDvdEioru24hCBX7ICXxVdLrsxXT9eouZREupVsni4AG6w1CIqqoPlm48aNfdqntBkGicXoKr6qV6MKo3a+Fjl2IEyKr+qt6J50BQv/q5IQSaX4CE4mZbLzWCI3XlM2YK+lvtfedL7WPjub1y9uIRYDGeZoInp9iaV2p0KefWWJ6TI5EEKIcPHHH3+4///gwYN59tlnOXDgAK1atQJg06ZNfPjhh0ycOFGrIYoSIsuexcdbP+b1ta9zLv0cAM0qNuONW9+g09W+z0tEmLhwEGb3hZM7XY9vHAwdR4FB5pMiNFgdauyAbwtuKdlr1JgM3hdf3ZmvcierKIA3axCoxVZ1DYIBAwYAedcgaN68OXD5GgS+CPR8U34zgsRi0pOS5X3ma0lZcCtZYgc0pdPpaFGjNAt3nWDLoYsBLb6meVh8VRSFxXu/ZIJxFf9nXAnoSKnUmNj/+x7iKhX85ELIlVkhhAgfTZo0QafToSg5d0y88MILl233wAMPcP/99wdzaKKEcDgdfP3H14xaNYqjSUcBqF26NvfE3cOr//cqZrNnmfMijO2ZCwsGgzUFIkvDPVPh2i5aj0qIPNRGL68zX3Ntb7U7MRm8jz6U8yvhiaFDh3LjjTcyfvx47rvvPjZv3synn37Kp59+CuRdg6B27drUrFmTkSNHXnENgqlTp2Kz2S5bg8AXgZ5vSqUrSHJWEPQsxLqoma9q8TUrDDJfs+wOd5FYYge0c32NUizcdYKtRwK76FZqZuHF18TMREb+cD/9//2dhkYFp6LD2nYwsbeM8ilm4FJJGa5ctoQoOVkSQohQd+jQIa2HIEooRVFYsH8BI1aMYO/ZvQBUia3CmPZjeLD+g/y65FeJLyrubJmwdDhszc6Srt4aek6D+CoFP08IDbhjB7ysIZgvWSA8Ov+4zgIlZ8cISuarKEiw1iDwRaDnm1J8DRKLybsM1qJmvqq3CliLkNsSLGoGKEjsgJZa1CgNwPYjF7E7nBh9uOLpiZTsztcrvdXbT27n26+7MTEthWidjrNKPM/aBjKzw/PgpzHJlVkhhAgf6q1oQgTT6sOreWn5S2z6bxMApSJKMaLdCAa2HEikKRKbzabxCEXAnTsAs/vA6d2ADtoNg/Yj/NIIIEQgqI1e3sYOGPQ6DHodDqfi852zyRmuczw5vxKFCdYaBN4K9HxT/nIESe4Qa08UNfPVkmtVNptDwWwM3eKr2gkZbTZg0IfuOIu7ayvEEhthJCXTzl+nUmhQJT4gr5N6hQW3FEXhs03vEfHrK7ypGAAdiZWa0vXQE5wlgbQsO2ajfzpVJfNVCCHC14kTJ1i3bh1nzpzB6cw7rxo8eLBGoxLFxY6TOxixYgRLDiwBINIYydBWQ3m+zfMkRCRoOzgRPH/8AAuHgC0NospCj0+hVketRyVEgXJiB7xvWLEY9aRbHUUovqqZr3J+JYoHf883pfgaJDnFV29jB4qW+QpgdTjzPA41Ke68VzlQa8mg19H8qlKs2n+WzYcuBK74mk/ma0pWCmNn96bfgdXUxYADsLYdRsItr5A6ehnYHKRm2SkV7Z/iq3S+CiFEeJo5cyZPPvkkZrOZMmXK5LmzR6fTSfFV+OzAhQOMXDmS7/Z8B4BRb6R/s/68ctMrVIotWta8CCPWdPjlBdjxletxjXbQ47MirzcgRDC4Ywe8zHwFV/0g3erwuF5xKTV2QM6vRHEQiPmmFF+DxJ3BavN2wa2iZb5CdtSBD7ktwZKSfaCWxba017JGaVbtP8vWIxd4rG3NgLzGpcXXP07t4vuv7+TV1CQiMZBqiSW697dE1mwHQEyEkQybI088RVElZhdfE6JkciCEEOFk5MiRjBo1iuHDh6PXh+6FZRE+TqSc4NXVr/L5js+xO11zjQcaPsC49uO4pvQ1Go9OBNWZv1wxA2f3ATq4+UW4+QXQ+9YMI0SwWR2+d77mrFHjW+er2twSFynn9CL8BWK+GRKz1g8//JAaNWoQERHBDTfcwObNmz163nfffYdOp3OvehbK1KtPVg8XwMopvvp28FJzW8DznFmtJLs7X+VArbWW2bmvWw5fzLPKnz+pRdQIvcJXWz9i7ydteD01mUh0XKzagpjBO9FlF14BYrPDYdWirT8kS+erEEKEpfT0dHr37h2QwmtJmI+KHBczLjL8t+HUer8WU7dNxe6007V2V3Y8uYNvenwjhdeSZsc38FkHV+E1pgI8Mh86DJfCqwgrWTbfMl8hZ5EuT+sVl5LzK1GcBGK+qXnx9fvvv2fYsGGMHj2a7du307hxY7p06cKZM2cKfN7hw4f53//+R7t27QrcLlRYvO18LWLsAORcvQr14qtaVIuR2AHNNaoaj9mg52xKFkcvpAfkNdT3e/+Z6bRZ+jK9FVfMQNrNL1DqsWUQXTbP9jERavHVfwtbJEnnqxBChKV+/foxe/Zsv++3pMxHBaTb0nlj3Rtc/f7VTFw/kQx7BjdWu5HVfVaz+IHFNKnYROshiiAyODIxLBgI858GWzpc3R6eWgdX36z10ITwmjt2wIcagrvz1cN6RW42h5O07OYxyXwVxUEg5puatxpOnjyZJ554gr59+wIwdepUFi9ezPTp03nppZfyfY7D4eDBBx9k7NixrF27lsTExCCO2DfqlaRgZb6CK3ogw+bw+epVsEjsQOiIMBloWDWebUcusvnQBa4qE+3317iYls5DhmW8krGKCJ2BZEssMQ/8QPRVN+a7fUx256tfYwdkwS0hhAhLEyZM4M4772TJkiU0bNgQkynvcXzy5Mk+7bekzEdLMpvDxvQd0xm7eiwnU08CUL9cfSZ0nMCd196ZJ89NlBBn9nLz/tHos06CTg8dRkDbYdLtKsJWTuarD7EDXt6pm1vu8zQ5pxfFQSDmm5r+ZlitVrZt28bw4cPdX9Pr9XTq1ImNGzde8Xnjxo2jfPny9OvXj7Vr1xb4GllZWWRlZbkfp6SkAGCz2bDZ/NdJVxhj9oQuPcuz103P7g406RWfx2k2ZL9mpjWoP6u3EtNc70+MWe/RONVtQvlnCmfNq7uKr7O3HqNbwwru+Ap/+G77p4y1zuVO01YAzlZuTsL93+KIKo3jCu9ntNk1EUhMy/Lbe56UYQUgyqiTz5EP5Hcw/IXbe2iz2VAUB05n4RcwFcXh/hsfLs/zRbi8d/42YcIEli5dynXXXQdw2QIIvgjGfBRCZ05a0jgVJ3P2zWHM6jEcuHgAgKvir2LUTaN4oP4DGPQG7HbvL/CG23FU5KIo6HZ+jfHX4cTaM3HGVMR5z6co1W8Eh9P1nwgL8nuYV4bVdSwz6LyvIai1gwwfagfnU1x3TEZbDChOBzYP5kEqeQ+vzJt5JWgzl7Xbi+eFy0DMNzUtvp47dw6Hw0GFChXyfL1ChQr89ddf+T5n3bp1TJs2jZ07d3r0GhMmTGDs2LGXfX3NmjXs3bvX6zH76swpPaBn9959/JxU+OuevWgAdPyxfSsZ//qWvemwufaxas1aDsX6tIug+OOw69/m7PFj/PzzEY+ft2zZssANqgQrmwFmvYHNhy8y6JOldLuq6BPQLGcWqw+/w7CkPVxj0GNTDPxe/i7Ol+8OqzYV+NzEc67Px7Zde0g4t7vIY3EqkJzh+t3YumENf5uLvMsSS34Hw1+4vIcpKSn8e1xPRHThf8wy01JYlvkvsbGxYfM8X5w7d86n54W7t99+m+nTp9OnTx+/7TMY81EInTlpSaEoCjtTdvLVya84mHEQgHhjPL0q9KJLmS6YjplYemxpkV8nXI6jwsXoyKDxsRlUveiaf56ObcT2q/pj3ZMIe37WdnDCZ/J76HLshOu8af/eP/n5/B6vnpua5Do/2rRlG1mHvKs/HEkFMGJW7Pz8s2+/R/IeXs6beSVoM5fdeKJ4zkcDMd8Mq57wlJQUHn74YT777DPKli1b+BOA4cOHM2zYMPfj48ePU69ePW666SZq1KgRoJFebsuifWw6c4waV9ema8dahW4/ad8ayMikfbsbaVw13qfXfPfvdVzISqfFDa1pWaOUT/sIhg3z/4STx2lYtzZdOxS+uIHNZmPZsmXceuutl7V/C/8oV/skQ2fv5rcTeu65uSmd61Uo/ElXsP/cXyz8phvvpF7AjJ7/lLIMsg7moco16Nq58Pdw6+K/2HL2KFVq1qJrp9o+j0OVlGFD2bQSgB533obZh9tySjr5HQx/4fYeXrhwgUNrDxIVm1Dotukpidza7mpKly4dNs/zxeHDh316XrizWCy0adNG0zH4Mh+F0JmTlgSbj2/m5ZUvs/roagBizbEMuWEIQ64fQqzFPx0J4XYcFcCp3Rjn9UN38SCKzoDtppfYlFSbWzt3kfcwTMnvYV4/nNkGF8/TolkTujau5PVz/005T/1GjenapLJXz1174Bzs3k6FUrF07Zp/lNyVyHt4Zd7MK0GbuWzrq4p+fh6KAjHf1LT4WrZsWQwGA6dPn87z9dOnT1OxYsXLtv/33385fPgw3bp1c3/N6XR15RmNRvbv38811+Qt3lksFiwWi/txcnIyACaTKai/3JFm1z+1TcGj183MDrqOjbT4PE41aNuJPqQPZKlW18+aEO3dzxrs97Akuad5dXafSGX6+kO8OPdP6lRO4JpyMV7v58ft0zAtGspwpw7QcbzS9XQ99DgZhliMOptH72F8pKs1NcOm+OX9TkvOjhwwG4iOtBSytSiI/A6Gv3B5D00mEzqdAb0HOXw6ncH9c4XL83wRDu9bIDz77LNMmTKF999/32/7DMZ8FEJnTlqc7T27l1dWvMK8v+YBYDaYGdhyIMPbDqdcdLmAvKa8f2FAUWDrNFgyAhxZEFcV3b3T0VVqBj//LO9hMSDvoYvN4epYjbZ4/+8RkV07cCg6r5+bbnO9bnyUuUjzGnkP8/JmXgnazGWNxrDq5/RYIOabmv5Lmc1mmjdvzvLly+nevTvgmrwuX76cQYMGXbZ9nTp12L07723Hr7zyCikpKbz33ntUq1YtGMP2iSU7wNrT1QPTs1cLjDIXbcEtAKvD88wVLagB3bGyMmJIGd61DntOJLH50AWe+mobPw1sQ7TFs0NGpj2T9398hPv2/UIN9NjQkd5hOOnXDSD53bWUshjR6TzL9YmJ8O+CW0kZstiWEEKEq82bN7NixQoWLVpE/fr1LztRmzt3rtf7LEnz0eLqaNJRxqwawxe7vsCpONHr9Dza+FHGtB9D9fjqWg9PaCkzCRYMhr0/uR5fezt0/wiiSoNkTIpiRl3cW13s2xvqc3xZcEs9v4qT8ytRTARivql5mXrYsGE8+uijtGjRguuvv553332XtLQ092qzjzzyCFWqVGHChAlERETQoEGDPM9PSEgAuOzroUYthKorEBZEURQybK4Dp3oFyhcmQ/YB1IPX1FJqputgHeNhYU8Eh8mg54MHmtJtyjr+OZPKC3P+4IMHmhYaMP3v+QPMn9mZoSnnMKHnfEQc8Q/NJb5qS/49ehHA4yIu5HwuUrP8M0FOTJfiqxBacTqdXq0In5CQgF4v0SAiR0JCAj169PD7fkvKfLS4OZd+jvFrx/Phlg+xOlx3ttxT5x5eu+U16pWrp/HohOaOb4c5feHiYdAb4dZx0Opp8HGxFCFCnVprMBu8ryGYs2sHnjaL5Zac4WqSkfMrUVwEYr6pebXr/vvv5+zZs4waNYpTp07RpEkTlixZ4l704OjRo8XixMti9LwQmrtAG1mUzleD5wVfLakdjXERmn8cxSXKx0bw0YPN6P3pJhbvPkmTtQk8cdPVV9x+0c4vMSx4hmFOAB0nq7ei0gM/QIQrtzg1+732ptAeK52vQhQbiYmJTF60w+MQ/2F3NvU5E1UUTzNmzAjIfkvKfLS4SLWm8s7Gd3hzw5ukWFMAaF+jPRM6TqBV1VYaj05oTlHg90/g11fAaYOE6nDvTKjaXOuRCRFQ6nm/L52vOXfNFqHzVe5kFcVEIOabIVHtGjRoUL63dQGsWrWqwOfOnDnT/wMKAIu787XwCIAMa842kUXofDV7UfDVksQOhLbmV5Vm5J31GDX/TyYu+YsGVeJpfU2ZPNtYHVY+nvso9/y5iOroyUJH2i0vU6nd//J0F6RmqcVXzz/XOZ2v/im+JmZPDhKi5PMmhBYiomOJjkvQehhCXKYkzEfDXZY9i0+3fcqra17lbPpZAJpWbMrEThO59epbC707R5QAGRdh/iD4a5HrcZ074e4PITJB02EJEQzqeb/FhwWF3TGJPtQOkjOluUWIwoRE8bUkUBe/8uRglp4dOWA26jHofZ9EFuXqVTClZB+sY6XzNWQ93Ooqdh5NZO6O4wyatZ1Fg9tSKT4SgCMXD7Foxq0MTD6DET1nI+JJePgnSldpdtl+fOl8dRdf/dT5miydr0IIEbZq1qxZYIHt4MGDQRyNCBaH08Gs3bMYtWoUhxMPA1CrdC1e6/Aaver3Qq+TrmQB/LcVZveFpKNgMEPn1+H6JyRmQJQY7sxXow+xA140i10qJ/NVzudF8RCI+ab8dgSJNxEAaudrUbpeITw6Xx1OhbTsnzdGiq8hS6fT8fo9Ddl3KoV9J5MZ8PV2vn+yFav+/A7D/KcZmB0z8N9VN1L1gR/Akv8txSnZ3ateZb6qsQN+6nyV2AEhhAhfQ4YMyfPYZrOxY8cOlixZwvPPP6/NoETAKIrCor8XMWLFCPac2QNApZhKjL55NI81fQyTQf6WC8DphE0fwm9jwGmHUjWh1wyo3FTrkQkRVGpeqy+dr0WpHUhziyhuAjHflGpXkLhXD/TgSlKmzT/FV0t2wdcWwp2vuW8ll87X0BZpNjD1oWZ0m7KOnccSeen9Efwv+SOqoCcTHamdRlG1zdACuwt86XxVs4P81fmamO5akCMhyuyX/QkhhAieZ599Nt+vf/jhh2zdujXIoxGBtPbIWoYvH876Y+sBSIhI4KU2L/HMDc8QZYrSeHQiZKRfgHlPwT9LXY/r3wPd3nOvNyBESVKUzFdv1qi5VLJkvopiJhDzTblHJ0i8yVDJUIuvRVhsC8Kj81WNHDAb9T7dHiGC66oy0YzsVplnDHN5K+kTqqDndEQ8hidXU7btsEJv60rNcr3fvmS+Ztgc2P1wISHnthiZHAghRHFx++238+OPP2o9DOEHf5z+gztm3cFNM29i/bH1RBojeanNSxwcfJAX274ohVeR4+gmmNrWVXg1WOCOyXDvDCm8ihLJ6VTccYPqXbfeyIkd8CXz1dUkEy9raohirijzTWk1DBL3gls2DzJfS1DsgLrYVpx0vYaFFbu/o/zip+hlUgD40dmOOr0/o0KlSh49P2fBLSNkePaauSMK0rIcxEcV7ZpRYnr2gltSfBVCiGJjzpw5lC5dWuthiCI4ePEgo1aOYtbuWSgoGHQGnmj2BCNvHknl2MpaD0+EEqcT1r8LK14DxQFlakGvmVCxodYjE0Izudd5sfhQR1ALtr7UDpKk81WUEEWZb0rFK0i8CbB2Z74WtfNVzZkNg9gBb25DF8Fnd9r5cl4/uu6eS0X0ZOh0TI8fzJunbqDq9/tYOKgMpaILv40/NStXvq+HxVdXV7SeLLuTlCxbka+oSuarEEKEr6ZNm+ZZAEFRFE6dOsXZs2f56KOPNByZ8NWp1FO8tuY1Ptn2CXana154f/37ebXDq9QuU1vj0YmQk3oW5j0J/y53PW54H9w5+YrrDQhRUuTuWPUl81Ut2HpbfFUURTJfRbETiPmmVLyCxJ2h4kEh1F+Zr+HR+eo6UMfKVbKQdTLpP5ZO70ifpJPo0XM8Mp6yjyzkofh6fP/BOo5eSOfZ73cyo09LDPpCYgcy1dgB7w49sRFGslKt7k7polCLrwlyW4wQQoSd7t2753ms1+spV64c7du3p06dOtoMSvgkKTOJNze8yTub3iHdlg5Al2u6ML7jeJpVaqbx6ERIOrwO5vSD1FNgjISuk6Dpw4XGXglREqhNXnodGAs5J8uPxeB5s1hu6VYHdqfrrsi4SCkvieIhEPNN+e0IEnfmqxexAxElovjqKqbJYluhad2fc9D9+Dh9nAqg49+abbnm/2aDOQoL8MnDzbnno/Ws+fss7/72N891vq7A/eXudPbmUxljMXIu1ZpngTZfSeerEEKEr9GjR2s9BFFEGbYMPtryEePXjedCxgUAbqhyAxM6TqBDzQ4aj06EJKcD1r4NqyaA4oSy17liBirU03pkQoQMtc5gMRrydOx5yuxFs1huydnNNSaDrsjNY0KEikDMN6XiFSTqioPeLLgVVcTYAVMRcluCJVmKryHJ4XTw3U9PcOsfsymPnjSdjqROY7mmTd5V/+pWimNCj4YM/X4XU1YcoHHVBDrVq3DF/arF9hiLkWQvxhOT/flILWLnq9XudF/cSIgsPCZBCCGEEP5hd9r5YucXjFk9hv+S/wOgbtm6vH7L63Sv092nYoEoAVJOw9wn4NBq1+MmD0LXN8Ecre24hAgxap1BrTt4y9fGrdx5r3IcF+LKpOIVJGYv2vj9FTvgTdSBVlLdxTjpQgwVZ1JOsGLaLTyYeBLQczQynnKPLqbyFRYxuKdpVXYeTeSLjUcY+sNOFg5qS42y+U+IczpfDV4VX2OzPx8pRex8VScHOp0U/IUQIpzo9fpCT+p0Oh12e9HvkBD+pSgKc/fN5eUVL7P//H4AqsVVY0z7MTzS+BGMevl7LK7g4Cr48QlIOwOmKLhjMjT5P61HJURIUusMat3BWxYfi6/JGa6/u3JXoSgOAjnflNlOkKhXoKx2J4qiFPiG+m3BrbCIHVAzX+WjGAp+//NHdHMfp3d2wX5/zbZc98CPYIoo8Hkv31GPPSeS2XbkIk9+tY15A28kynz5e+rrAmv+6nxNyrACriuzeh+ykIQQQmhj3rx5V/zexo0bef/993E6Q3e+U1ItP7icl5a/xNYTWwEoE1mGl9u9zICWA4gwFjy3ECWYww6r34A1bwIKlK8Hvb6ActdqPTIhQpa/Ol89uVM3N7W5JVaKr6IYCOR8UypeQaJmvjoVsDsVTIYrF378lvkaBrED6m3ocVJ81ZRTcfLj/P7csvMHyqAjRacj8dZxXHfjYI+ebzbq+ejBZtw5ZR37T6fw0o+7ea93k8tWCHR3Onv5fsdmF2tTs2xePe9SkvcqhBDh6e67777sa/v37+ell15i4cKFPPjgg4wbN06DkYn8bD2xleHLh/Pbwd8AiDZF81zr53juxueIs8RpPDoR0pJPwo/94Mh61+Nmj8Ltb4ApUttxCRHi1HN+te7gLV9rB8lyfiWKkUDON6XiFSRqGz+4riaZCrgdwF+Zr76GZgdTTuerHKy1cj7lFKun30Kvi8cBHYci4ynf52eqVWjg1X4qxEXw4QPNeOCzTSzYdYIm1RJ4rG1N9/ez7E73Spjadb7K5EAIEXqcTieJiYleP6ekOnHiBKNHj+aLL76gS5cu7Ny5kwYNvPubJQJj/7n9vLLyFebsnQOASW9iQIsBvHzTy5SPLq/x6ETI++c3mNcf0s+DOQa6vQcN79V6VEKEBXfnq9HH2IHsxi9fO1+lmUoUN/6eb8pvSJDkzl7JsjkKLD75K/PV11sHgsl9G7ocrDWxfe88+LEfPRyuz9yemu2o/8AcdIXEDFzJ9TVLM6JrXcYt2sv4n/fRoEo819csDeR0Oet0EOXlZ1v9fSlq5mtiumtykBAlxVchROhITExk8qIdRETHerR9ZloKPRuWDvCoQk9SUhLjx49nypQpNGnShOXLl9OuXTuthyWA/5L/Y+yqsczYOQOH4kCHjocbP8zY9mOpkVBD6+GJUOeww8rXYN07rscVG8K9M6FsLU2HJUQ4ycquIfhafM1Zo8bLztdMaW4RxUug5ptS8QoSvV6H2aDH6nAW2omqZr5GFLXzNfsAagvhztfk7IKcZL4Gl6IoLJj/JDft/I5S6EjS6bjY+TUatB5U5H33bVODXf8lMn/nCZ7+ZjuLB7elQlxETqHdbPQ6b1Utzqf4qfM1TiYHQogQExEdS3RcgtbDCFmTJk3ijTfeoGLFinz77bf53hYmgu98+nkmrpvIlM1TyHJkAXDXdXfx+i2v06C8dCMLDyT9B3P6wbFNrsctH4fOrxe63oAQIq+sosYOuNeLKXyB8Nzk/EoUJ4Gcb0rFK4gsRlfxNctWcDE0XY0d8FPnazhkvkrsQPBcTDnFuukdufvif4COA5HxVOjzCzUq1PfL/nU6HRN6NOSvkynsP53C099s59snWvmc9wq5Ml+LWHx1d77K5EAIIcLKSy+9RGRkJLVq1eKLL77giy++yHe7uXPnBnlkJVOaNY13N73LpA2TSM5KBqBd9XZM7DSRG6vdqPHoRNjYvwR+egoyLoIlDu56H+rfo/WohAhLavHV7GvsgI+RhckZrvMz6XwVxUEg55tSfA0ii0lPSlbhrfyZ2Z2vkf7KfA3p4qua+SofxWD4Y998mNOXbtkxAztrtqPxgz+iM1r8+jpRZiNTH27OXVPWse3IRcb/vI/O9SsA3ue9Qq7M1yLGDkjmqxBChKdHHnkkzyKOQhtWh5XPtn3Gq2te5XTaaQAaVWjEhI4TuL3W7fIeCc/YrbB8LGz8wPW4clO4dwaUrlnw84QQV5RlL1rsgCVXZKGiKB4fz3MyX+X8SoS/QM43peIVROotAFmFtPJn+Cnz1derV8GkFtNifSjICc8pisKSBQO4cccs4tFxUafjfOdXadL6mYC9Zs2y0bxzfxMe/3IrMzcc5myq63ZE3zpfXX/Mi5r5qk4OJPNVCCHCy8yZM7UeQonmVJx8u/tbRq4cyaHEQwBcXepqXu3wKr0b9Eav8+1kX5RAF4/AnMfg+FbX4xsGwK1jwc+NAEKUNGrDlcXHGoLauKUoYHcqmAyeFaAk81UUJ4Gcb0rFK4g8XQBLLb5GFDV2wOB6fqh2viqKIrEDQZCUeppN0zpy+8VjgI6/IuOp1HcJtcrXC/hrd6pXgWduqcWUFQdY/MdJoIidr9l/3H0lna9CCCGE5xRF4ZcDvzB8+XD+OP0HABWiKzDq5lE83uxxzAazxiMUYWXfIpj/NGQmQUQ83P0R1L1T61EJUSzkZL762vmaU3uw2p2YDJ7tJ9md+SqlJSEKIr8hQWTxMAZAXXArqpjHDmTYHDicCiCxA4Gy969FMPtRujhcRe4tNdvR4sG56IzBO1ka0uladv2XxJq/zwK+vddqwbaosQOJ6VYA4iPlZFEIIYQoyPqj6xm+fDhrj64FIM4Sx4ttXuTZG54l2hyt8ehEWLFnwbJR8PtU1+MqLaDXDEioru24hChG1HVlfC2+5s6KzbI7ifawGT1ZmluE8IhUvIIoJ0fFw9iBIhZf1VsFQrX4qna96nVFLzSLvBRFYcXCp7l++zfEouO8TsfZzq/RsvWgoI/FoNfxfu8m3DllHf9dzPApDyg2wj8LbknnqxBCCFGw3ad38/KKl1n490IAIowRPHP9M7zY5kXKRJXReHQi7Fw4CLP7wsmdrsc3PgMdR4NB5mJC+FNO5qtv59UGvQ6DXofDqXhVP5DMVyE8I8XXIHJnvto863wtauarO+YgRDNf1eJrjMUoCzT4UWraWbZM60DHC66YgT2R8VTpu4Q6QYgZuJKEKDPT+7Tk/eX/8OANV3n9fLXzNc3q6pY26H37vCTJapxCCCFEvg4nHmb0qtF8tesrFBT0Oj2PNXmM0e1HUzWuqtbDE+Hoz3mwYDBkJUNkKbjnE7i2i9ajEqJYUmMHzD52vgKYDXoynA6Pi692h5O07NqFnF8JUTApvgaRJ5mvTqfiv8zXXLED3qxYGCwp2fmdkvfqP//8tQhl9qN0cNhxorCpZjtaPTQPfQhksl1bIZYPHmgGgM3mXXZr7kW6UrPsPv1xVxSFpAxX7IAsuCWEEEK4nEk7w+trXufjrR9jc7r+Pt9b715e7fAqdcrW0Xh0IizZMmHpCNg6zfW4Wiu4dxrESxFfiEDJ6Xz1vfhqMenJsDkKvVNXlZzrrkSJERSiYPIbEkSeZL7mLswW9VZ8iyHn+TaHgtkYasVXdbEt+Rj6w5r5A2i+4xui0XFGp+N059e4sfUzWg/LLyxGA2aDHqvD6XPxNcPmwOZwZQzLlVkhhBAlXXJWMm9veJu3N75Nmi0NgE5Xd2L8LeNpWaWlxqMTYevcAZjdB07vdj1uOww6vAwGme8LEUhqjcFiKlrnKxS+QLhKzXuNsRgxerhAlxAllfwVDCL1QFjQlSS16xX81/kKYHU4i3QLQiCoxVfJhyma9LRzbJvWgZsuHAV07IiMo1qfpTSsoF3MQCDERhg5n2b1Ofc1Md01OTAZdJIxLIQQosTKtGfy8ZaPeX3t65zPOA9Ai8otmNBxAp2u7qTx6ERY+2M2LBoC1lSIKgs9PoFa8pkSIhjUgqmvma+Q685ZD2MLc/JepawkRGHktySI3JmvBVxJUouvZqPe51xLVe5iq83uBA9XLAyW1KzsK2VysPbZwf2LUX54hHYOOw4U1tZsy00PzUdfDBcxiFGLr1neRRaoci+2FWoRHEIIIUSg2Z12vtr1FaNXjeZY8jEAritzHa/f8jo96vaQv43Cd9Z0WPIibP/S9fiqttDzc4irpO24hChB1HVlihQ74MGdurklZ8cIxsldhUIUSqpeQeRJG3+G1dXVV9TFtuCSFQtDcNEtiR0oAkVh08KBNNr+NVHoOKWDk51fo33rwVqPLGDURbdSitj5KpEDQgghShJFUZi/fz4jlo9g37l9AFSJrcLY9mN5tMmjGPUyDxNFcHa/K2bgzF5ABze/ADe9IDEDQgSZendtkRbc8qBZLDd356ucXwlRKPmrGEQ5sQMFFV9d3/PXbdHerlgYTMlSfPVJZto5dk27hVYXjgA6tkTGcVWfJTStUF/roQWUWnxNzfKt+Jq781UIIYQoCVYdXsVLv73E78d/B6BURClGtBvBwJYDiTRFajw6EfZ2zoLFz4EtHaLLQ8/P4Or2Wo9KiBIpJ3agKMVXLztfMyRGUAhPSdUriNQDoSeZr/7ofAXXAdS1YmHoFV9Tsm9TiJWDtceO7v8Z5w+PcIPDhh2FlTXbcMtDCzAUw5iBS6lFel8zX5MyrAAkRJn9NiYhhBAiFG0/uZ0Ry0ew9N+lAESZohjaaij/u/F/JEQkaDs4Ef6sabD4f7BrlutxzZuhx2cQW0HbcQlRgvkj89Xb2AFpbhHCc1J8DSJ35qut8MzXoi62pfL26lUwqUU0taNRFEBR2LZwEPW3f0UEOo7r4HjnV7m19bNajyxoiho7IJMDIYQQxd2BCwd4ZcUrfP/n9wAY9UaebP4kr9z0ChVjKmo8OlEsnN4Lsx+Fc3+DTg/tR0C7YaCXxUyF0JJ6vq/ebesLT5rFcsvJfJXzeSEKI78lQWQ2epH56sfYAfB8xcJgUotosjpiwbLSzvHntFtonh0zsCEylpp9lnJ9MY8ZuJS6MFuKj7EDkvkqhBCiuDqRcoJXV7/K5zs+x+60o0PHAw0fYGz7sVxT+hqthyeKA0VxLaj1ywtgz4TYSq5FtWq01XpkQghyCqZFih0weBs7IOdXQnhKql5B5Ekbv9r56q/MV29vHQimlCyJHSjM8b8W45z9KM0cNmwo/FrjRro8vACjoeTdOh9jcX1OfI8dkMmBEEKI4uVixkUmrZ/Ee7+/R4Y9A4Cutbsy/pbxNK7YWOPRiWIjKwUWDYXds12Pa3WCez6B6LLajksI4eaX2AGTd41b7gW35HxeiEJJ8TWIPMp8zV5wy1+xAyYvr14FU4osuHVlisIfCwdx3favsQBHdXDs1nHcceMQrUemGXfma3bR3ltSfBVCCFFcpNvSmfL7FCaun0hiZiIAN1a7kQkdJ3DTVTdpOzhRvJz8A+b0hfMHQGeAjiPhxmdB73t3nRDC/9RoQ390vhYUk5ibuoC2nF8JUTj5qxlEluyCaoGxAwFYcAvA6vAstyWYJPM1f7bUs/wxpTGNsguvqyNj0T21jjYluPAKuYuvRet8TYiSyYEQomSbOHEiOp2OIUOGuL+WmZnJwIEDKVOmDDExMfTs2ZPTp0/ned7Ro0e54447iIqKonz58jz//PPY7XmPyatWraJZs2ZYLBZq1arFzJkzg/ATlRw2h41Ptn5Crfdr8dLyl0jMTKRB+QYs6L2AdX3XSeFV+I+iwJbP4fNOrsJrXBXo+zO0HSqFVyFCkF9iB4w+dr5K8VWIQknVK4jcV5I8yHz1V+xAKC+4lezufJWDterU/sU4f3iURg4bVhQW12jNHQ8twGy0aD00zcmCW0IIUXRbtmzhk08+oVGjRnm+PnToUBYvXszs2bOJj49n0KBB9OjRg/Xr1wPgcDi44447qFixIhs2bODkyZM88sgjmEwmxo8fD8ChQ4e44447eOqpp/jmm29Yvnw5jz/+OJUqVaJLly5B/1mLE6fiZPafs3ll5SscuHAAgBoJNRjXfhwPNHwAgyx2JPwpMwkWPgt/znM9vvY26P4xRJXWdlxCiCvyS+yAsfBmsdxS5PxKCI9J8TWI3BkqBcUOZHe++it2wJOCr1ZSMtXMV/kYoijsWziIWtu/xgQc0sGRW8dyz41DtR5ZyFCLr752vqoLbknnqxCipEpNTeXBBx/ks88+47XXXnN/PSkpiWnTpjFr1ixuueUWAGbMmEHdunXZtGkTrVq14tdff2Xv3r389ttvVKhQgSZNmvDqq6/y4osvMmbMGMxmM1OnTqVmzZq8/fbbANStW5d169bxzjvvSPHVR4qi8Ou/vzJ8+XB2nNoBQLmocoy8aST9m/fHIhdnhb+d2AGz+8DFw6A3Qqex0Hog6HRaj0wIUQC12UqtOfjC7EFMYm45na9yPi9EYeSekSDy5EqSmvkaWcw7X612p/vfoaQHdNvTzrJ3ShPqZhdef4uIgSfX0F4Kr3nEqLED0vkqhOacTicXLlzw+D+nM7T+BhUnKSkpJCcnu//Lysq64rYDBw7kjjvuoFOnTnm+vm3bNmw2W56v16lTh+rVq7Nx40YANm7cSMOGDalQoYJ7my5dupCcnMyff/7p3ubSfXfp0sW9D+Gd3//7nVu+vIXbvrmNHad2EGuOZWz7sfw7+F+eueEZKbwK/1IU+P0TmNbZVXiNrw6PLYUbB0nhVYgQZ3c4sTsVwE+xAx7UDhRFITlTzq9E0QQyCivUyCWKIHIvuFVAgHWGzfWB8Xfmq82h+GV//pK7ezHaUnJvlTv712Kcsx+lnsNGJgrzr2pF94cWYDFFaD20kBNrcf1R9yV2wOnMPTkw+3VcQpREiYmJTF60g4jo2EK3zUxLYdidTSldWm5XDYR69erleTx69GjGjBlz2Xbfffcd27dvZ8uWLZd979SpU5jNZhISEvJ8vUKFCpw6dcq9Te7Cq/p99XsFbZOcnExGRgaRkZFe/Wwl1b6z+3h5xcvM+8t1y7fZYGZgy4EMbzucctHlNB6dKJYyLsL8QfDXItfjOnfC3R9AZCltxyWE8EjujNaixA6YvVisO8PmcNcYSnozlfBNIKOwQpEUX4PI4kEbf4bV9T3/Z76G1oJbauRAlNmA0VACG7CdTv5ZOIiaO77BCBzQKRzsNIr72/xP65GFrJgiLLiVkmlHyb7+IFdmhfCPiOhYouMStB5Gibd3716qVKnifmyxXN4NeezYMZ599lmWLVtGRIRc3At1vxz4hXl/zUOv0/No40cZ034M1eOraz0sUVz9txXm9IXEo2AwQ+fX4Pr+0u0qRBjJ3dxlLkLna05MYuHF1+QM1zmZUa/zW+1ClByBjsIKRSWw6qWdnAyVgjpf/Zv5ajF4t2JhsKS4F9sqefV/R8pp/v6gKbWzC6+/RERD/zV0lsJrgXJnvjqd3nVyJ2ZYAVexvygTEiGECDWxsbHExcW5/8uv+Lpt2zbOnDlDs2bNMBqNGI1GVq9ezfvvv4/RaKRChQpYrVYSExPzPO/06dNUrFgRgIoVK152y5f6uLBt4uLipOvVC0+3fJrHmz7O7gG7mX73dCm8isBQFNgwBaZ3cRVeS9WAfr/CDU9K4VWIMKPWF4x6HQa977+/3qwXk5P3akInx4wSz5sYLAh8FFYokipEEKm3ABR0JSkj+6qVv2MHQi3zNdm92FbJ6kI8v28hF9+tz7UXDpOBwpdXtaT9sAPUqtRE66GFvNyF+jSrd92vkvcqhCjJOnbsyO7du9m5c6f7vxYtWvDggw+6/7/JZGL58uXu5+zfv5+jR4/SunVrAFq3bs3u3bs5c+aMe5tly5YRFxfnjj5o3bp1nn2o26j7EJ6JMEbw2V2fUa9cvcI3FsIX6Rfg297w6yvgtEO97vDkGqjcVOuRCSF84F5sq4hNJhYvageS9ypyq1evHvHx8e7/JkyYcMVt1Sis/LbxVxRWKCp5bYcaUtv4C15wKzvztZgvuKUumqR2MxZ7TgeHFj5D9R3fYAD2o3Cg4ys80u4FrUcWNixGPSaDDptDITXL7lXhXoqvQoiSLDY2lgYNGuT5WnR0NGXKlHF/vV+/fgwbNozSpUsTFxfHM888Q+vWrWnVqhUAnTt3pl69ejz88MNMmjSJU6dO8corrzBw4EB3t+1TTz3FBx98wAsvvMBjjz3GihUr+OGHH1i8eHFwf2AhxJUd3QRz+kHyf2CwwG0ToMVj0u0qRBhTYw0tRWzgcjeLeXDXbFJ6dudrCbyTVVzOkxgsKNlRWPKbEkQeZb5mxw74rfiq3jogsQOacaac4vD0zlx98QgA8yOiuO7hRdxRpbnGIwsvOp2OGIuRi+k2V/E+3vPnJqZL8VUIIQryzjvvoNfr6dmzJ1lZWXTp0oWPPvrI/X2DwcCiRYsYMGAArVu3Jjo6mkcffZRx48a5t6lZsyaLFy9m6NChvPfee1StWpXPP/+cLl26aPEjCSFyczph/buw4jVQHFD6Gug1Eyo1KuyZQogQl+WnzlezB/UKldr5GifnV4KcGKzC5I7CUjkcDtasWcMHH3zA0qVL3VFYubtfL43C2rx5c579XhqFFYqKf+UrhOTOfFUUJd9sFHXBLX/FDphCtPNVXXCruK+MmLh3Ac4fH+Nqh400FL6t3oL/e2gh0eZorYcWlmIiXMXXFC8X3ZLOVyGEyGvVqlV5HkdERPDhhx/y4YcfXvE5V111FT///HOB+23fvj07duzwxxCFEP6Sdg7mPQkHfnM9btgL7nwHLLHajksI4Rfuzlc/FV89qR3kznwVwlNqFFZuffv2pU6dOrz44otUq1bNHYXVs2dPIP8orNdff50zZ85Qvnx54PIorFAkxdcgUtv4FQXsTgWT4fLia6a/M18NoVp8Leadr04HRxcMourOWeiBP1HY32E4j988XOuRhbUYiwnIcMdWeEqdHCREyeRACCGEECXI4fXwYz9IOQnGCOj6JjR9WGIGhChGsrJrCEVdWNirzNcM1/mYNLcIbwQrCisUFdPKV2jKfSUqy+7EZLj84JheUjJfs4pv5qsz+Tj/zbid6tkxA7MtkdR9eCE9qrbUeGThLzb785LiY/FVJgdCCCGEKBGcDlg7GVaNB8UJZa+FXl9AhdDtChJC+CYndqBoNYTcd+oWxt35WszvZBXB548orFBU/CpfISxP8dXmyLfw6M589VPnq/vqVYhlvia7O1+L18E6ee9POH98nOoOG6kofFGtKY88tIhYua3LL2KyO6VTs2xePS8x3QpAQpTZ72MSQgghhAgpqWfgx8fh0GrX48YPwB1vgcReCVEs+S3z1Yu7ZtXMV2luEUUVqCisUCPF1yDS6XSYDXqsDme+V5OcTiUndqCYd76qma/FJnbAYef4goFU2fUdALtwsq/9izx988v5ZvsK36ifF187XyWTSAghhBDF2sFV8OMTkHYGTFFwx9vQ5AGtRyWECCB35qupiLED2Q1gXnW+RhaT83khAkx+U4LMYnQVX/MrhuY+yPk789UWYp2vauxAcSi+Kkn/cWLm7VS5eBSAbywR1H9oPr2rtdJ4ZMWP2i2e6uWCW4np2ZmvUnwVQgghRHHkdMDqN2D1JECB8vWg10wod53WIxNCBJjfYgcMnscOJEusmxBeCf/KV5ixmPSkZOV/QFPzXgEi/FV89SK3JZiKy4JbqX/OxTm3P1UcNpJR+LxqY/o9tIj4iHith1YsuWMHJPNVCCGEEMIl+STMfQIOr3U9bvYI3PYGmKO0HZcQIij8FjvgvmvWUei2kvkqhHfCu/IVhtSrUVn5HNDUvFeLUY9B759b1UM/diBMD9YOG6cXDKTCru8B2I6T3Tc9x9AOoyVmIIBifex8VScHCVFh+nkTQgghhMjPgd9g7pOQfg7MMXDnu9Col9ajEkIEUVZ2HcFcxOKrN+vFqM1U0twihGek+BpkBXWiZqqLbfkp7xVyhWaHWOxAOHe+KhePcPqLO6mY6IoZmGG20OChuTxava3GIyv+1NiBFB+LrzI5EEIIIUSx4LDDytdg3TuuxxUaumIGytbSdFhCiODzV+erJVfjlqIoBTYVyZoaQngn/CpfYc5SQCdqujW7+OqnyAEI3c5X9bZxtZgWLjJ2z8Ex70kqOu0kovBxlQY89dBiSkWW0npoJUJMdqe0N7EDVrvT/bslxVchhBBChL2k/2BOPzi2yfW4RT/oMh5MEdqOSwihCau/Ml+zawdOBexOBZMh/+Kr3eF034ko51dCeCa8Kl/FgMXd+ZpP7IA1AJ2vIVh8dToVUq1q52uYHKztVs7Of5pyu2cDsBkHu9oO4aWOr0rMQBC5O1+zYys8oV6V1enC6PMmhBBCCJGfv5fCvCch4yJY4qDbe9Cgh9ajEkJoyN+Zr+CqH5gM+e8vJVcjTDjeySqEFuQ3Jcjcma+2y4uhauarPztfvcltCZZUqx1Fcf3/cDhYKxcOce7LbpRLPAbAp2YzDR+YwxM1btZ4ZCWP+nnxJvNVLb7GWox+y1IWQgghhAgqhw2Wj4UNU1yPKzWBXjOg9NWaDksIoT21sctiKmLx1ZC3+BptyX+75OxGmGiz4YoFWiFEXqFf+SpmPMp89WPxVT0YhlLnq3qlzGzQE+HHnzUQMnd9j3P+05Rz2rmAwvuV6jHo4UWUjSqr9dBKJHfx1YvYgaQMKwAJUeaAjEkIIYQQIqASj8LsvnB8q+vxDU/BrePAeIXKiBCiRMnyU+yA0eBa+NvhVPKtV6gk71UI70nxNcg8ynwt5rED7rzXUO56tWVyYf4ASu+ZC8B6HOxsM4hRncaj18nVPa34suCWLLYlxJU5nU4uXLjg8fYJCQno9XIMFEKIoNm3COY/DZlJEBEPd38IdbtpPSohRAhR76o1FzF2AFwNUhlOR4H1g+QMyXsVwlshXP0qntRbAfLNfA1A56s5JDtfs28DD9Xi6/l/Of/lXZRJ+g+AD8wmGvWey8CrO2o8MBGTK3agsBU4VYnprs9bQpRMDoS4VGJiIlOW7iEiOrbQbTPTUhh2Z1NKly4dhJEJIUQJZ7fCslHw+8eux1Waw70zoNRV2o5LCBFy3LEDfii+Wkx6MmwOrI7L6xUqd+errKchhMdCtPpVfLkzX/MphgZywa2sEMp8VWMHQrH4at35Lc4FgyjjtHMWJ5MrXseQhxZTIaaC1kMTQKzF9QdeUVyd4tGWwj9DcluMEAWLiI4lOi5B62EIIYRQXTgEc/rCiR2ux60HQcfRYJQIJSHE5ax+ih2AnOatzHzWqFGpma9yfiWE50Kv+lXMqQezYGW+qsVXm8PpcadgoKkHa7WQFhJsGST+NICEP+cBsAY7W1sP4LVb38CgD+1c2pIkwpSTQ5SaZfeo+OrufJXJgRBCCCFC3Z8/wYJnICsZIktB96lw3W1aj0oIEcJyMl/9EDvgwYLdOc0tUk4SwlPy2xJk7tgB2+Vt/Grmqz8XobIYXPtSFLA7FUwG7Yuv6kr1IZP5evZvEr/uTkLScZwovGsy0vj+HxhWq4vWIxOX0Ol0xFiMJGXYSMm0USEuotDnSOarEEIIIUKeLRN+fRm2fO56XK0V3DsN4qtqOy4hRMhzxw6Y/BA74MGaMclyfiWE10Kk+lVyWAqIAVAzX6MCEDsArgOoyaD9QimhFDtg3f4lyqIhJDgdnMbJGxVq87+HFlE5trLWQxNXkFN89WzRLXVyIJmvQgghhAhJ5/+F2Y/Cqd2ux22HQoeXwSBzFyFE4dTOV7MfzvXNBcQkqiTzVQjvaV/9KmHcma/5ZKgEMnYAXMXXaIvfdu0zdcEtTQ/W1jSS5z1J3L6FACzHzuYbHmdSl7cx6uXXIpTF5lp0yxOJcmVWCCGEEKFq9xxY+CxYUyGqDNzzKdTupPWohBBhRK0tWPxQRzB70vma3QQj51dCeE6qTEHm7nwN0oJbBr3OnZFZUG5LMGne+XpmH8lf9yAu+QQOFN40GWh87w8Mv+4ObcYjvOIuvnrY+SqxA0IIIYQIObYM+OVF2P6F6/FVbaDn5xAnd18JIbzjjh3wQ+arxVB48VUWNBbCe1J8DTKzu/ganMxXcN1+kOF0FHgADSa1aBbjwWJJfqUo2LfPxLn4OeKcDk7gZHz5q3nxwUVUi68W3LEIn6mfmxRPO1/TrQDER8oKwUIIIYQIAWf/dsUMnNkL6OCm5+HmF8Egp2ZCCO+pTVZ+Kb6arlyvUEnmqxDek7/wQVZQgHUgMl/BVfDNsDkKzG0JpmR352sQD9ZZqaTO60/MX4sBWIqdjS368s7t72CSPK2wEpP9ufG881VuixFCCCFEiNj5LSweBrZ0iC4PPT6FazpoPSohRBhzxw4Y/RA74EHna7I781XKSUJ4Sn5bgkzNYcmvEBqIzFfAvchWqHS+qpmvQYsdOLWb1G/uJSblFHYUxhv1NLn3G8bU6R6c1xd+pXa+epL5qigKSRmuzldZcEsIIYQQmrGmwc/Pw85vXI9r3gQ9PofYCtqOSwgR9tTagtq1WhTuzNcCIguTs8/n4+X8SgiPSfE1yArKfHXHDvi589XiwQE0mIKW+aooOLZ8jvOXF4lRHPyHk7Flr+LlhxZRI6FGYF9bBIw3C25l2BzYHAogna9CCCGE0MiZfTC7D5z9C3R6aD8c2j0Hev/O+YUQJZMaEaB2rRZFQXfqgtrcEgILaAsRZqT4GmTuzFfb5RkqGQHqfPVkxcJgUotmAS2+ZiaTPq8/Uft/wQAsxsb6Zg/z4R1TMBsk+zOcuTNfs6+4FiQx3bWNyaDze5yHEEIIIUSBFAV2fAU/vwD2DIip6FpUq2Y7rUcmhCgmFEUJSOfrlSILM21OaW7xktPpJDEx0avnJCQkBGQsQjtSfA0yNYclvy7UTGuAMl9DNnYgQAfrEztJm3Uf0amnsaEw1qijyT0zGV//vsC8ngiqnOJr4Z2vSbnC4HU6XUDHJYQQQgjhlpUCi4bB7h9cj6/pCPd8AjHltB2XEKJYsTkUFFct1D+Zr4UUX9XzK4Nemls8lZiYyORFO4iIjvVo+8y0FIbd2TTAoxLBJsXXIHPHDtiuvOBWwDpfHVdesTBYFEUJXOyAouD4fSrK0hFEK06O4GRUmaqMfHAhtUrX8u9rCc14Ezugdr7KVVkhhBBCBM2p3a6YgfMHQGeAW16BNkNAX/SuNCGEyC13U5daaygKd7PYFYqvat5rXIRRmlu8EBEdS3RcgtbDEBqS4muQ5WS+Xl4IdWe+Bix2QPHrfn2RaXNid7rG4dfO14xEMuY+TuQ/ywD4CRtrm/Tmkzs/IsIY4b/XEZpzF1+97HwVQgghhAgoRYGt02HJcHBkQVwV6DkNrmqt9ciEEMVU7jhDfxRfzQXUK0DOr4TwlRRfg+xKbfxOZ05WS8BiB0Jgwa2ULNfBWqeDKH8Vmf/bRsZ3vYlMPYMVhVcMCk3v/py3Gz3gn/2LkBJjcf2h96TzNVkmB0IIIYQIhsxkWDgY/pznely7C9wzFaJKazsuIUSxptYQzEa9XzpRC4ssVM+v4uT8SgivhMS9Lx9++CE1atQgIiKCG264gc2bN19x288++4x27dpRqlQpSpUqRadOnQrcPtRcqY0/M9eVpUh/F19DaMEtNXIgxmJEry/iHwdFwblhCo5pnYhMPcNBnDxSuiKPDdjC/0nhtdiKifA88zUxwwpAQpQssiaEEKJgJWk+KvzsxA745CZX4VVvhM6vwf99J4VXIUTAuRfbMvintKMu2nWl2oF0vgrhG82Lr99//z3Dhg1j9OjRbN++ncaNG9OlSxfOnDmT7/arVq3i//7v/1i5ciUbN26kWrVqdO7cmePHjwd55L5RD2aXdr5mWHOKrxF+CMrOLRSLr3FFjBww2VOxf3cf+l9fwaA4mYONyQ27M33ATuqUreOPoYoQpS645Unnq0wOhBBCeKKkzUeFnygK+i2fwbTOcPEQxFeHvkvgxmck31UIERRqPIBaZygqtfP1SgtuuTtfA7V4thDFlOazgsmTJ/PEE0/Qt29f6tWrx9SpU4mKimL69On5bv/NN9/w9NNP06RJE+rUqcPnn3+O0+lk+fLlQR65b66U+armvVqM+qJ3hF4ip/iq/YJbKdkB3UVZbEv332ba7HuRyIMryUJhiN5B2t0f8UHPr4gyRflrqCJE5V5wS1EKzjGWBbeEEEJ4oqTNR4UfZCbR8tAUDL8OB4cV6twJT62Bai21HpkQogRRF/K2+KmBy1JI41ay2kwl51dCeEXTzFer1cq2bdsYPny4+2t6vZ5OnTqxceNGj/aRnp6OzWajdOn8b+vJysoiKyvL/TglJQUAm82GzWYrwuh9o1dcB7EsuxOr1erOZUnJcI0xymzw+7hM2bXcDKtdk585t8Q0188Z7cvPqTjRbZyCfuVrxKPwDw5eTKjIqPvmUL9cfc1/NuE59b3y5T2z6F0FV4dTITk9kyjzlQ9jiWmu2IEYi14+H35UlPdPhIbc76GiOHA6C784pygO999OeZ52z1Ofa7fLCsP+Eoz5KITenFT4Tnd8O4Z5/aicdAxFb8LZaSzOFk+4FjWQ9zJsyHwm/Ml7COlZrvMds0Hnl38Hg851rpVpy792cDH7fD7G7J/zq5LwHvoyz1P/PXx5XjDnsjIf9Zymxddz587hcDioUKFCnq9XqFCBv/76y6N9vPjii1SuXJlOnTrl+/0JEyYwduzYy76+Zs0a9u7d6/2giyjdDmBEUWDR4l9Qo1mOpmZ/3W7l559/9utrnj6pB/Ts2buPn5OD/zPntumMDjCQkXzBq5/TbEum0eGPqJLqGv+32PiqVHMeqTaQI1uOcIQjARqxCKRly5Z5/RxFAR0GFHTM//lX4guIcz1wzPXZP/L3Xn6++KfvAxX58uX9E6Fl1apV/HtcT0R0bKHbZqalsCzzX2JjY0lJSZHnafQ89bkbT5zzaFtRuGDMRyH05qTCB4rCNWeXUO/4D+hxkGYuz9aaT5N4tir88ovWoxM+kvlM+CvJ7+H+RNf5dVZGml/qCPvOuvZ34vSZfPe394Dr/Ork0X/5+ecDRX49VXF+D32Z5y3L/BfAp+cFcy4r81HPaVp8LaqJEyfy3XffsWrVKiIiIvLdZvjw4QwbNsz9+Pjx49SrV4+bbrqJGjVqBGmkObJsDoZvcd2S1uHWzu78ys2HL8DurZSOi6Zr17Z+fc3NC/ex8cwxalxTm64da/l13946veEI/Lufq6tVpmvXRh49R3d0I445Q7BkXCADhef0dvRV+jK79yTMZllIKRzZbDaWLVvGrbfeisnk/S0ro3auIDnTzg1tbubqctFX3O7zo5sgKZl2rVpwy3XlijJkkUtR3z+hPfU9bN++PYc2HSMqNqHQ56SnJHJru6spXbo0Fy5c4NDag/I8DZ6nPrf1VbU92lYEnifzUQi9OanwUsZFDAsHoT++FAD7dXeyynInHW67W/4WhimZz4Q/eQ8hYv9Z2LeDsqXj6dq1VZH3p9tziq8O/EFcQmm6dr3+su8vmrUTzp6hZeMGdL2+WpFfryS8h77M825tdzWAT88L5lxW5qOe07T4WrZsWQwGA6dPn87z9dOnT1OxYsUCn/vWW28xceJEfvvtNxo1unIRz2KxYLFY3I+Tk5MBMJlMmvxyG405/+RO9O4xWJ2udu1Is9Hv44rIvi3brqD5AS3N6opdiI8yFz4WpxNl7dsoK1/HiMJfOHg+vhyje83m+LbjmM0e7EOENF9/D2MjTCRn2sl0FPyZTspwZRKVjY2Qz0oAaHUcFf5jMpnQ6Qzo9YXnhOl0Bvd7Ls/T7nnqc3PPJ0TRBGM+CqE3JxVeOPo7zHkMkv8DgwVuG4/S+BHsv/wi718xIO9h+CvJ76FDcdURIoz+qSNEWVzNTTaHku/+UrIXPS4d49/zq+L8Hvoyz1P/LXx5XjDnsjIf9ZymC26ZzWaaN2+eZ3ECdbGC1q1bX/F5kyZN4tVXX2XJkiW0aNEiGEP1G51Ol+8KgpnZC25Fmf0TlJ2buZDQ7GBSV6iPKWzBrdQz2L68C93K19Cj8CVWxtftwjdP76JxhcZBGKkIZWrHuPp5upKkDFlwSwghRMFK4nxUeMjphHXvwozbXYXX0tfA479By8dd+a5CCKExdSFvi8k/pR11P1lXqB2ozS2y4JYQ3tG8TD1s2DAeffRRWrRowfXXX8+7775LWloaffv2BeCRRx6hSpUqTJgwAYA33niDUaNGMWvWLGrUqMGpU6cAiImJISYmRrOfwxsWox6rw5nngJZhcx00I0wBKL4aQqf4mpLpKobFRRRwsD64GuvsPpgzLpCOwmC9nWa3v80XLQag0/knSFyEN7V4n5J55eKr06mQnKkWXyWeQhRvTqeTxMREj7ePjr5yXIcQJVFJnI+KQqSdg3lPwYHsHMIG90K3d8HiWfaeEEIEg3qObzH6p/haWO0gWZpbhPCJ5sXX+++/n7NnzzJq1ChOnTpFkyZNWLJkiXvRg6NHj6LX5xxIPv74Y6xWK/fee2+e/YwePZoxY8YEc+g+s5j0pGTlPaClZ3e+Rgai+Jp9ILY5QqH46iqWxebX+ep0oKx+A1ZPwozCHhwMiyvNhN7zaF65eZBHKkKZJ52vKZl2FNdinTI5EMVeYmIikxft8Dgc/5kuDYIwKiHCR0mcj4oCHF4PP/aDlJNgjIDbJ0GzR6TbVQgRcrLcxVf/1BHU2sGVOl/V4mtcYXeyCiHyCInfmEGDBjFo0KB8v7dq1ao8jw8fPhz4AQWYemBUbxEAyMzufI0MQOyAJYRiB65YfE05hX12H4xHNwIwDSu/XncrP9zzJQkRCUEepQh1OZ2vV+6CViMHIk0G9yRCiOIsIjqW6LgErYchRNgqafNRkQ+nA9ZOhlXjQXFC2Wuh10yoUF/rkQkhRL6ybP7tfFVrFdZ8GrccTsWd+SrNLUJ4JySKryWNJZ+rSRnByHwNhc5XNfPVkutgfWA5tjmPYcpMJBWFgTorTbtM5LsbnkUnHQYiH7Fq52sBsQOJGVYAEqJkYiCEEEKIQqSegblPwMFVrseN/w+6vgUWiZEQQoQuf2e+ujtfbY7Lvpe78UUyX4XwjhRfNZBzQCu5ma+xEUZw2FFWjod1kzGhsAsHQ2ITmHD/HFpVbaXxSEUoUzunC4odkMW2hBBCCOGRg6tdhdfU02CKchVdmz6o9aiEEKJQakOXes5fVJYCGreSsxfbijIbMPnp9YQoKaT4qoGcA1rO1aRgZL5eKbclmNTYgVL2szhm/h+GY78DMBUry2p34MceX1M6srSWQxRhQO2cTimg+JqYLsVXIYQQQhTA6YDs9QZAgXJ1XTED5etoPTIhhPCIO/PVT3WE3JGFiqLkuRM1KcODxbOFEPmS4qsG3JmvuTpf3ZmvASy+hkrna3v9Dmr++BSGrGSSUXhSl0XTTq8y+8b/odfJFTRRODXztaDYAel8FUIIIcQVJZ90dbseXut63PRh18Ja5ihtxyWEEF6w2v2b+arWDpwK2J0KJkNO8TU5U86vhPCVFF81oOax5Ml8DeCCW+7YAY0zX23WLIYoX/OUeRFkwTYcDI6J5Y37fqZt9baajk2EF3fmqwexA5L5KoQQQog8DiyHuf0h/RyYoqHbu9DoPq1HJYQQXnNnvvq5+Aquwm7ueAF352uklJGE8Jb81mhALYaqB0rIWXArEMVXUyh0viYeQ/n+UZ4ybgNgCjaWXtOGn3rMolx0Oe3GJcKSdL4KIYQQwmsOO6waD2snAwpUaOiKGShbS+uRCSGET9S7adW7a4sqd3as1e4k2pLzvWQ5vxLCZ1J81YDa+WrNr/M1ALEDFq0X3PrrZxzznsSclUyyEsXztj5Uuy2aBe1GSMyA8ElMdudrwZmvVgASosxBGZMQQgghQljScfixHxzd6Hrc4jHoMgFMEdqOSwghisC94JafOl+NBj0GvQ6HU7lszRjJfBXCd1J81YA78zV38TW78zUqELEDBaxYGFB2K/w2GjZ9hAHYohgZah1PamQFPrmpa3DHIooVtfM1JTt3KD85t8XI5EAIIYQo0f7+FeY9CRkXwBwLd70PDXpoPSohhCgyf8cOgKv7NcPpuKx5S818lfMrIbwnxVcNqAfG/DJfI4rLglsXD+Oc/Sj6EzsBmEwW88p3479j5bk6WhYyEEXjTear3BYjhBBClFAOGywfBxvedz2u1NgVM1D6ak2HJYQQ/qLWFNS7a/3BbNSTYXNgdTjyfF2aW4TwndzzrQG1GJply5X5GsDYgaAXX/fOx/FxG/QndnIBhbtJJ/HmF3il/ZsAxMptCqKI1M9QaqYdRVHy3SYxPXvBLZkcCCGEECVP4lGYcXtO4fX6J6HfMim8CiGKFXfx1U+Zr659Xd4sBpCc4Wp8keYWIbwnna8acB/MHJfHDgRiwS01NDvgsQO2TPj1FdjyGQZgA3aejozkjZ6z6VKrC3O3/wdAXIR87ETRqLED9uwsovw6xiUQXgghhCih/loMPz0NmYlgiYe7P4B6d2k9KiGE8Luc4qt/O19z71uVk/kq5/NCeEs6XzXgzny1XR47ENDM10B2vp7/F+e0TrDlMwDeIIsR1ZuyeMAuutTqAkBK9sr0sXKwFkUUZTKg07n+v/q5ulRi9uQgIUqKr0IIMWHCBFq2bElsbCzly5ene/fu7N+/P882mZmZDBw4kDJlyhATE0PPnj05ffp0nm2OHj3KHXfcQVRUFOXLl+f555/Hbs97HF61ahXNmjXDYrFQq1YtZs6cGegfTwgXuxV+eQm+e8BVeK3SHJ5aI4VXIUSxpd5N68/O1yvVD9TMV2luEcJ7UnzVQL6Zr9YgZL46nFe8RbtIds/B+Uk79Kd2cw4nXUnnYtsh/NZnFVXiqrg3U/M51ZXqhfCVXq8jxnzl3Fer3Ul69u+UTA6EEAJWr17NwIED2bRpE8uWLcNms9G5c2fS0tLc2wwdOpSFCxcye/ZsVq9ezYkTJ+jRI2dRIofDwR133IHVamXDhg188cUXzJw5k1GjRrm3OXToEHfccQcdOnRg586dDBkyhMcff5ylS5cG9ecVJdCFQzC9M/z+setx60HQdwmUqqHpsIQQIpDUAqnZj52vaiH30uKrZL6KogpmM0CokSqYBnLa+F3FIUf2rdMQmMxXi8G1T0Vx3aZtMuj8s2NbBix5CbbNRA+swc7TEWYm9pjHndfeednm6pUyyXwV/hATYSQly05qPp2v6sRAp5PPmxBCACxZsiTP45kzZ1K+fHm2bdvGTTfdRFJSEtOmTWPWrFnccsstAMyYMYO6deuyadMmWrVqxa+//srevXv57bffqFChAk2aNOHVV1/lxRdfZMyYMZjNZqZOnUrNmjV5++23Aahbty7r1q3jnXfeoUuXLkH/uUUJsXc+zB8EWckQkQD3TIXrbtd6VEIIEXDBjB2QzFdRVGozQMuWLbHb7YwYMYLOnTuzd+9eoqOjAVczwOLFi5k9ezbx8fEMGjSIHj16sH79eiCnGaBixYps2LCBkydP8sgjj2AymRg/fryWP16BpPNVA5ZL2vgzcy28FZDM11wHYr9FD5z7B+WzjrBtJk4UXiOLEVUb8vOAXfkWXkFiB4R/qR3UKVm2y76nFl9jLUYMej9dbBBCiBCUkpJCcnKy+7+srCyPnpeUlARA6dKlAdi2bRs2m41OnTq5t6lTpw7Vq1dn48aNAGzcuJGGDRtSoUIF9zZdunQhOTmZP//8071N7n2o26j7EMKvbJmw+H/wwyOuwmu1G+CpdVJ4FUKUGGpDl8Xkx85Xw+WxA4qiuNfUkM5X4aslS5bQp08f6tevT+PGjZk5cyZHjx5l27ZtAO5mgMmTJ3PLLbfQvHlzZsyYwYYNG9i0aROAuxng66+/pkmTJtx+++28+uqrfPjhh1itVi1/vAJJ8VUDluzuVvVKUkau4muEH7NaVH4vvu76Hucn7dCd+ZPTOOlCOhdaP82KvmuoHl/9ik/LKb7KwVoUnbroVn6Zr0kZroNuQpQ5qGMSQohgq1evHvHx8e7/JkyYUOhznE4nQ4YMoU2bNjRo0ACAU6dOYTabSUhIyLNthQoVOHXqlHub3IVX9fvq9wraJjk5mYyMDJ9+RiHydf5fmHare70B2gyBPoshoZqmwxJCiGDK6Xz1Xx1BLeRaHTl1iiy7072At3S+ikuFWjNAKJIWRA1cmvmak/eqRx+ALj2DXodBr8PhVNwHTJ9Y0+DnF2Dn1+iBFdgZYDEysfts7ql7T6FPT83M6UYUoqjUIn5BsQMyMRBCFHd79+6lSpWcfHWLxVLocwYOHMiePXtYt25dIIcmRODsngMLh4A1BaLKwD2fQu1OhT5NCCGKm4DEDmR3vuZeIFw9vzLodUQH4G5dEd7q1auX5/Ho0aMZM2ZMgc8JZDNAKJIqmAbcGSrZHa9q52sg8l5VJkN28dXXztcz+1BmP4ru7H6cKIwli18qNeCX+2ZzdamrPdqFxA4If1KL+PktuJWY7pocJERJ8VUIUbzFxsYSFxfn8faDBg1i0aJFrFmzhqpVq7q/XrFiRaxWK4mJiXkmvKdPn6ZixYrubTZv3pxnf+oCCLm3uXRRhNOnTxMXF0dkZKRXP5sQl8m13gAAV7WBnp9DXGVNhyWEEFpQlJzz+0BkvuZu3HJHDkQY0ekk1k3kJc0AhZPYAQ24Vw905O18DWTx1X31ytviq6LAjq9xftoe3dn9nMRJR9I5f/0TrO23wePCK0jsgPCvmAKKr7ISpxBC5KUoCoMGDWLevHmsWLGCmjVr5vl+8+bNMZlMLF++3P21/fv3c/ToUVq3bg1A69at2b17N2fOnHFvs2zZMuLi4twdD61bt86zD3UbdR9C+Ozs35C93gDo4Kbn4ZEFUngVQpRYuc/tzYEovtov73yV8yuRH7UZQP2vsOKr2gywcuXKKzYD5HZpM0B+F/rV74UqKb5qwB07YMub+RqIxbZUZrXg603xNSsV5j0J8weit2fyK3bamHUM6DWLD7p+gMVY+NWM3NQiWYx0vgo/KDjzVWIHhBAit4EDB/L1118za9YsYmNjOXXqFKdOnXLnsMbHx9OvXz+GDRvGypUr2bZtG3379qV169a0atUKgM6dO1OvXj0efvhhdu3axdKlS3nllVcYOHCge5L91FNPcfDgQV544QX++usvPvroI3744QeGDh2q2c8uioFd38Gn7eHMnxBdDh6eB7e8AgaZUwohSq7cxVe/Zr4aL2/cSs6U8ytRdMFqBghFMmPRQM7B7JLYgQAWXy353DpQoFN7UGb3QXf+HxwojCSLXyrUYel9c6hdprZPY1AP2BI7IPwhp/PVdtn33LEDMjkQQggAPv74YwDat2+f5+szZsygT58+ALzzzjvo9Xp69uxJVlYWXbp04aOPPnJvazAYWLRoEQMGDKB169ZER0fz6KOPMm7cOPc2NWvWZPHixQwdOpT33nuPqlWr8vnnn9OlS5eA/4yiGMq13gAANW+CHp/B/7d332FOlen/x99JZpLpDCNdEVAQUWYFQVlsgMuKBRuirm3BjoINQcA2LKyA2AvKivX3XSwrKusCoohgAZUVGXdRYKlWQBAGpqad5/dHSJheUyYzn9d15bpMck7OE59MuHOf+9xPeuOtbBERiZZgPsFmC7QZDBdnJcnXUOWrrmKVBhg9ejSvvvoq//znP0PFABAoAkhOTi5TDJCVlUVGRga33HJLlcUAM2fOZMeOHRWKARojZcFiwHWgvUD5Bbci2nbgwBeot6bkqzGw+mXMe3dh83v4CYvLKKZHn2tYeeYTJCfWr1+bZZlQ5auSrxIOwc9RZQtu7Vflq4hIGcaYGrdJSkpi1qxZzJo1q8ptOnXqxKJFi6p9nYEDB7JmzZo6j1GkjF/XwZsjYdd6sNlhwEQ4bRzYtdCLiAhQpt9rOPuwOh0Vr5rdXxz4zaXfV9IQ0SoGaIyUBYuB8v1Xg8nXpCj0fK227UDJflhwO6x9CxuwCC+jEm1MO/dlrvzdlQ06fqHHR/B3n86WSThU1/M1r1gLbomIiMSlA+sNsGg8+IohrV1gUa0up8Z6ZCIijYo7lHwNbx7BlVj2Sl0o3fNVKSSpv2gWAzQ2+suJgeCXWTARGmw7kBLRnq81JF+3fxNoM7BnCz4Mk3CzuHVX3r9kHj1a92jw8YMJsgS7LawrMUrzFez5ul89X0VERJoGdwEsHAv/eSNw/8jT4cLnIK11bMclItIIBdeQCffv68oKt/ZrwS2RBlHyNQbK93wt8Uav7YC7fPLVGPj385j378bm9/A9Fn+imO69ruSLs2eR6kwNy/GDiyKlJyWE9ZIIab7SD1RQV9Z2IK/IA0CLZGdUxyTSEJZlVVjZsyaZmZnY7TqhJSJNwI618OYI+G0T2Bxw+j1w8h2g7zgRkUoF8wnOcCdfKyncUs9XkYZR8jUGgpcFuH0WxhiKPJFfcCt09qp0z9fiPHj3Flj3Ljbgn3i5KcHwwDlzuLr31WE9fn5osS19WUt4VNd2YJ96EkkcysvL49EFa0hKTa/V9iWF+Ywd2pusrKwIj0xEJIKMgdUvwXsTwe+G9A4w/EXo1D/WIxMRadTcvshUvla2WHdw8Wz9vhKpHyVfYyB4JskY8PpNqO1AcmLkpqPC2aufV2PevBpb3vd4MNyFm8WHdOb9S+aR3TY77MffX6LFtiS8QgtulUu+GmPYVxyofFXPV4k3SanppGZkxnoYIiLRUbIf/nUbfPt24H63IXDBs5B6SGzHJSISByLW8zV41ay3kspXJV9F6kWZsBgofWbK47dCC24lOyN3WVUo+er1w+fPYJbcj83ysgWLSymiW/al/Hvo30h31a7iqq6Cl4YHqxVFGipU+Vqu7UCx14/XH2jkrTOzIiIijdQvuTDvatizBewJ8Icc6D9GbQZERGopWFgVXFMmXJyVVb7qykKRBlEmLAZKJ1/dXv/B5Gske7467LSggFNW3wq7lmMD5uFltMNiylnPcEOfGyLai/Vgz1d9WUt4BBfc8vgt3D5/6Ixv8Kxsgt0W0UXsREREpB6MgVVz4IN7wO+BFh1h+EvQ8YRYj0xEJK4Ee76Gv+1A4DdU5T1fm28Kqb7rM4iAkq8xYbPZcCbY8fgs3D4r1HYgKYLJ126e75jkyuGwXbtxYxhLCe+37MjiS+bRu33viB03KNjztTl/WUt4pToPfpYKSny40gJ/P3lFgc9aZkqiFncTERFpTIrz4N0xsO5fgfvdz4Hzn4YU9a4WEamrYFuAcLcdcJZbIBzU8xXqvz6DCCj5GjMuR8Xka4ozAtNhWfD5U9zy/V9w2PxsMSkMt/3KEcdcyOrzXqBFUovwH7MS+er5KmHmsNtIdToo9PjJL/FxSJoLUD8iERGRRumn1TBvJOT9APZEOGMq9BsFOlEqIlIvwZ6vzjBXvoYW6z7w+n7LhH7PN/ffWFqfQepLmbAYcSXayXcHvtBKvBHq+Vr4G8wfBRs/wAH8y/97buEQ7hzanzEnjolqVWBwUaQ0JV8ljNKTEin0+MssuhWqfG3mgYGIiEijYAx88QwsyQHLC5md4OKX4NA+sR6ZiEhci1TbgYOVr4Hka+k1NjLURlCkXpQJi5HgpQFun5+iSPR8/X4lZt612PJ/oQTDJF9f3vHdwvnHp3BLv9PDd5xaCl6moJ6vEk5pSQmw/2BlNcD+Yl0SIyIi0igU7YF/joYNiwL3e5wH5z0FyZkxHZaISFMQTI6Gu+1AMJkbrHwNXlmYnOgIe5WtSHOh5GuMuEqdTQouuBWWnq+WBZ89ilk2DZvxsx4/l1CMK+t0+NXGIcntGn6MelDbAYmENFfg81Sm8rXYA0BmijMmYxIRERHgx1Xw5tWw/ydwOGHINDjhOrUZEBEJk2By1JUY2crXYCFVRrJ+y4vUl/56YiT0heY92HagwT1fC3bB29fDlmXYgP/Dwxibl/v/OBN74VCeWLoJj99f48tEQr4qXyUCgsn8Arc39Ng+Vb6KiIjEjmXByidh6RQwfsg6Ai5+GdofF+uRiYg0KZFuO+Dxl6181e8rkfpT8jVGQqX8fn9owa0GtR3Y+gnmreuwFeykCMNoSvgwow3vXfwPTup4ErOWbQoc78DZq2gLViamu/SRk/AJVb6WVOz5quBAREQkygp/g3duhE1LAvd7XgRDH4ekjJgOS0SkKXJ7I7PgVqhF4oE8RbCtm/q9itSfMmExcvALzTrY87U+C25ZfvjkIczHD2IzFt8eaDNweLczWHPh/9EqpdWB45Xt2xJtajsgkRBMvuaXajugM7MiIiIx8P1KmHct5P8CCUlw1oNw/Ai1GRARiZCI93z1l207oN9XIvWnTFiMBPuyuH1WqPK1zj1f83fAW9fBtk+xAS/g4Tabh3tO/ysTTpmA3XYwmVv+0oFoO5h81Re2hE9aUsXK12DyNTNFnzUREZGIsyz47BFYNg2MBYd0C7QZaNcz1iMTEWnSIt52oNyCWxlKvorUm5KvMeJ0BL7Qir3+0JdanXq+bv4I3r4BCndRgOEmSvgw/RAWXvQ6AzoPqPJ4sah8NcaU6vmqj5yET7CNRX4lyVedmRUREYmwgl8D8eiWZYH7v/sTnPMIuNJiOy4RkWYgtOBW2NsOBF7PMuDzW+wvDvzW0u8rkfpTJixGgpWvwUQR1LLnq98Hy6djPn0EG4b/HGgzcNgRg8gdNpe2aW0r3a38ioXR5PZZeP0GOFipKBIOwUrqArUdEBERia4tHwcWei3YCQnJgaRr7ytiPSoRkWYj1HagIWvHVKJ0D1m3zzpY+arf8iL1pr+eGAn2Zdlb5Cn1WA1nrPb9HGgz8MNKbMBsPIzFzYSBOdx72r047FV/6SbGsPI1WJVos0FaXap7RWoQTObnV7LgltoOiIiIRIDlh49nwscPAgZa9wi0GWhzdKxHJiLSrLgjVPkavGoWAvmDYM9XtR0QqT9lwmIk+AW570CiKCnRjt1ezYIEG5cELusq3sN+DDdQzEepLXn3on8x+IjBNR4vlj1fgy0H0pwJ1b9HkToKLrhV4A58xizLKDgQERGJlFLrDQDQ+0o46yFwpsR2XCIizVCker4mOOw47Db8lsHjt9TzVSQMlHyNkeAXZLBKr8p+r34vfDQVVjwBwNf4uZRiOnQ+hdyLXqNDeodaHa980+xoOrjYlj5uEl6hBbcOtB3IL/FhAh0u1HZAYsayLPLy8uq0T2ZmZkTGIiISNqXWGyAxFYY+BsddGutRiYg0W25vZCpfIVD9Wmz5cXst9qutm0iDKRsWI8FkaF5xoO1Apf1e836EedfAT6sAeBoP4yhh7KmTmDJoCgn22k+fK4ZtB4KJMfV7lXALLrhVcCDBHzwrm5zoCLX2EIm2vLw8Hl2whqTU9FptX1KYz9ihvSM8KhGRejqw3gCfPgIYaNsz0GagVbdYj0xEpFk72HYg/L97nAn2wOLgfn+pnq9KvorUl7JhMRL8gswr1XagjPWLYP5NUJLHPuAailieksE7F77NWd3OqvPxgslebwzbDqTry7rR8Pv9eL3emjeMEK/XS0JCAiUlJfj9/nq/TorD4tB0B6kJFiUlJezNL+DQdAet01yUlJSEccRSWrjmr6EcDgcJCQnYbI2vnUlSajqpGZmxHoaISMOUWm8AgD5Xw5nTITE5tuOSJsEYg8/ni1ks0VjiGam/xjCHsYxHPRHq+QplF+zef6DQRZWvIvWn5GuMhHq+Biv1nAfOVvk88OFk+GIWAKvw8yeKaNfx9+QOf4OOLTrW63ixbDuwX20HGpWCggJ++uknTPD6/BgwxtCuXTt+/PHHBgUqfsti8qA22GywdetWLK+fyYPakOiwsXXr1jCOWEoL1/yFQ0pKCu3bt8fpdMZ0HCIiTc7/PoB3boTiPeBMh/OegJ4XxXpU0kR4PB62b99OUVFRzMbQmOIZqZ/GMoexikdDPV/LF3KFgatU8vVgz1f9nhepL/31xEjwCzLU8zUxAfZuC7QZ+Hk1AI/hZgJubj3pTqb/YTqJjvqfaYrtglvB5KvOlMWa3+/np59+IiUlhdatW8csSLEsi4KCAtLS0rDb6x8s+PwW1q4CADq1TaegxIt9XwnJTgeHZ6WGa7hSTrjmryGMMXg8Hnbt2sXWrVvp1q1bzMYiItKk+L2wdAqsfDJwv/1xMPwlOOTI2I5LmgzLsti6dSsOh4MOHTrgdDpjEpM2hnhGGibWcxjreDTSbQcg8Fs+WMClyleR+lPyNUacB3qwFnsDZ6tO8a2E2U+Aex97gREU8WlyGvMu+AfndT8vbMdzx6Ln64Hka3Bleokdr9eLMYbWrVuTnBy7SwYty8Lj8ZCUlNSgAMUYgy0h0DfZ6XTh8NuxJVg4nYkkJSWFa7hSTrjmr6GSk5NJTEzk+++/D41HREQaoNx6A5x4I5wxFRJcsR2XNCkejwfLsujYsSMpKSkxG0djiWek/hrDHMYyHg3+tndGaMEtgF35bgDsNkitapFwEamR/npixHVggS0nXu5OmMvI3R8A8Dk+/kQxbQ/ty5qL/0HnzM5hOV4s2w4Ee75mqO1Ao9FULq2y2WzYbTYsY/Abg98KtFJw2JvG+5Oa6ceSiEiYlFpvAFcLOP9pOKbhBQAiVdG/4dJUxOqz7D5QyBWJnq/BfEUw+ZqRnIhdv7FE6k3ZsBhxJdjpZNvB04lPkm3fBsCDuLkXNzf1u4WH/vgQrjBWGZRuO2CMiWryLV89XyWCHHYblt9gWYEELECCAgMREZHa8Xngwxz44pnA/Q7Hw8UvQcvOMR2WiIhUL5JtB1wHKl93FxxIvqqFoEiDKBsWI513vM8C5z2k24rZY9K4yX8ii9M+4rXz/s7wY4aH/XguR+AL2RjwWYZERxSTr+5A5at6vkok2A+cSPAb8PtV+SoiIlJre7fBm1fDL18H7v9+NAyeDAlaxFBEpDHzWwbfgav+IlH5GizeCla+qt+rSMMo+Rpt3mJYPInjV78ENlhldedWzxj2Zqxn9Q0P0TWra0QOm5hwMBnl8VkkOqJ3aUS+er42apZlkZeXF9VjZmRkhO21gh/l0pWv4U6+btu2jS5durBmzRp69eoV1teur/Xr1zNy5Ehyc3M5+uijyc3Njdqx//KXv/D222/zzTffRO2YIiISZt+9C/8cA+59kJQJFzwLR58d61FJMxXv8Wg0KB4ta/LkycyfP5/ly5dH7ZiNSel2gsHFvMPJVS75mpGs3/IiDaG/oGjavRHeHAk712IBz/jO5zHfcPw4uLH3FRFLvMLBhtkQ+KJOjeK6CWo70Ljl5eXx6II1JKWmR+V4JYX53H72cSQk1P7zMHLkSF555RWmT5/OxIkTQ4/Pnz+fCy+8kG9+3ItlDp79bQ6Vrzk5OaSmprJhwwbS0tKieuw777yTESNGRPWYIiISJt4SWHIfrHoucP+wE2H4i5DZMbbjkmatKcSj5kARQHMSy3h03LhxjB49OqrHbEzcPn/ov50RKKwKVb4WqPJVJByUDYuWb96ABXeAt5DdNhjpb81a36WhpzOSIpsNTXDYsdvAMoG+r9EUXHBLbQcar6TUdFIzMmM9jGolJSXx4IMPcuONN9KyZcsKz/ut+Ftwy+Px4HTW79LOzZs3c84559CpU6eoHK+0tLQ0LCv6i/eJiEgD/bY5UAiw4z+B+yffBqffBw7FaBJ7TSEejUfxHI+mpKSwf//+Br9WPAr2e3XYbSREMPmqnq8i4aElJiPNUwT/HA3v3ADeQpbhI9vksyWrW5nNkhLD3yS7vNCiW75oJ19V+SoNN3jwYNq1a8f06dMrfd5vDE/MnMYlQ04tk3x9/PHH6dy5c+j+yJEjueCCC5g2bRpt27YlMzOTKVOm4PP5GD9+PFlZWRx22GG89NJLFY6xfv16TjrpJJKSkujZsycff/xxmefXrl3LWWedRVpaGm3btuWqq65i9+7doecHDhzImDFjuP3222nVqhVDhgyp9L1YlsWUKVM47LDDcLlc9OrVi8WLF4eet9lsrF69milTpmCz2Zg8eXKlr1PV8aob53PPPUeHDh0qJFfPP/98rrnmGiDQduDUU08t8/zzzz9Pjx49SEpK4uijj+aZZ54JPTd8+HDGjBkTun/77bdjs9lYv349EAjCU1NT+fDDDwGYN28e2dnZJCcnc8ghhzB48GAKCwsrfY+RZFkWe/bsqdNNSWkRabTWvgV/GxBIvCZnweVvwh+nKPEqUgc1xaMQuBy+fFsAxaPhj0cnT57M8ccfX+b5phiPVsXtDS62FZmUTvB184oChVSqfBVpGCVfI+nX9TDndFjzdyxgMm4GU8TZva/m78NeKbNpcjSSrwfOiEW78rXAreSrNJzD4WDatGk89dRT/PTTTxWetywTutyrpsrXjz76iF9++YVPPvmERx99lJycHIYOHUrLli358ssvGTVqFDfeeGOF44wfP54777yTNWvW0L9/f84991x+++03IHC53Omnn07v3r356quvWLx4MTt37uSSSy4p8xqvvPIKTqeTFStWMHv27ErH98QTT/DII4/w8MMP85///IchQ4Zw3nnnsXHjRgC2b9/Osccey5133sn27dsZN25cle+1/PFqGufFF1/Mb7/9xrJly0KvsWfPHhYvXswVV1xR6THmzp3L/fffzwMPPMC6deuYNm0a9913H6+8EvieGzBgQJl+XB9//DGtWrUKPfbvf/8br9fLSSedxPbt27nsssu45pprWLduHcuXL2fYsGExuZQveAnkM8s21er26II1Ue9XJyJSI28x/Ot2mHcNePLh8JNg1Gdw1BmxHplI3KkpHq0LxaOKRxsi2HYgUslXZ7nXzWhCyde6FliouELCQdmwSDAGcufCwnHgK2anzcZlpoAvEp28eM7LjOg1gs27CsrskuyMfB7cmeAAfFGtfPX5LYo8gX8Y1HZAGurCCy+kV69e5OTk8MILL5R5zmcZguGQw1Z98jUrK4snn3wSu91O9+7dmTlzJkVFRdx9990ATJo0iRkzZvDZZ5/xpz/9KbTfmDFjuOiiiwB49tlnWbx4MS+88AJ33XUXTz/9NL1792batGmh7V988UU6duzI//73P4466igAunXrxsyZM6sd38MPP8yECRNCx37wwQdZtmwZjz/+OLNmzaJdu3YkJCSQlpZGu3btqn2t8sf761//WuM4zzrrLF599VX+8Ic/AIEz/61atWLQoEGVHiMnJ4dHHnmEYcOGAdClSxe+++47/va3vzFixAgGDhzIbbfdxq5du0hISOC7777jvvvuY/ny5YwaNYrly5dzwgknkJKSwvr16/H5fAwbNix0CVt2dna17zGS4uESSBGRKpVabwBscNo4GDARHPoJIFJf1cWjdaF4VPFoQwTbDrgSIlPE5XSUfd2mlHytS4/pksJ8xg7tTVZWVhRGJk2ZIq9wcxfAwjvhP68DsAQ/V5oislp3Z9XFb9KzTU+g4hmq5MTIT4UrBm0HglWvoMpXCY8HH3yQ008/vcLZda//4Jnomipfjz32WOz2g3+Dbdu2pWfPngf3dzg45JBD+PXXX8vs179//9B/JyQk0LdvX9atWwfAN998w7JlyypdbGDz5s2hYLdPnz7Vjm3//v388ssvnHzyyWUeP/nkk/nmm2+q3bcy5Y9Xm3FeccUVXH/99TzzzDO4XC7mzp3Ln/70pzL/z4IKCwvZvHkz1157Lddff33ocZ/PR4sWLQDo2bMnWVlZfPzxxzidTnr37s3QoUOZNWsWEKg8GDhwIADHHXccf/jDH8jOzmbIkCGcccYZDB8+vMn0VRMRiZpS6w2Q2hqGPQdHnh7rUYk0CVXFo3WheFTxaEOEkq+JUap8bWK/5VVgIdHWtP6CYm3HWph3Nez+H37gfkqYjocrjruSZ895ljTnwX9cyp+hSnZGsedrFNsOBPu9JiXaSYxAI3Bpfk477TSGDBnCpEmTGDlyZOhxj8/CZrdjjMFWqvLV6/VWeI3ExLJnbm02W6WP1eUSk4KCAs4991wefPDBCs+1b98+9N+pqam1fs1wKH+82ozz3HPPxRjDwoULOeGEE/j000957LHHKn39goJAFf+cOXPo169fmeccB86Y22w2TjvtNJYvX47L5WLgwIH87ne/w+12s3btWlauXBn68eJwOFiyZAkrV67kgw8+4KmnnuKee+7hyy+/pEuXLg37nyEi0hx4iuC98bDm74H7nU+Fi56H9Oor00Sk9qqKRwHsB+LR0hSPKh4Nt0i3HSj/uur5KtIwSr6GgzGw+mVYPBF8Jeyw2bjEFLAqIYHnzp7Dtb2vLZMMgopnkqLa8zWKla/B5GuaS1/WEj4zZsygV69edO/ePfSY12+RlXUIv+36tUwCNjc3N2zH/eKLLzjttNOAwJn01atXhxr3H3/88bz11lt07tyZhIT6f7VmZGTQoUMHVqxYwYABA0KPr1ixghNPPLFhb6CW40xKSmLYsGHMnTuXTZs20b179woLGgS1bduWDh06sGXLlip7cEGgz9acOXNwuVw88MAD2O12TjvtNB566CHcbneZygqbzcbJJ5/MySefzP3330+nTp145513GDt2bMPevIhIU/frukCbgV3rARsMnAinjQd75ONMkeamsngUoHXr1uzYsUPxaDUUjzZcsPK1fF4hXJpyz1eRWFDytaFK9sOC2wMryALv4efPpoiWh3Tly4vf5Lh2x1W6W8W2A1GsfI1q8jVwlrepXabQ1JQU5sfVsbKzs7niiit48sknQ49ZxtC3/ynsuXc8M2fOZPjw4SxevJj33nuPjIyMBh8TYNasWXTr1o0ePXrw2GOPsXfv3tCKq6NHj2bOnDlcdtll3HXXXWRlZbFp0yZef/11nn/++dBZ99oYP348OTk5HHnkkfTq1YuXXnqJ3Nxc5s6d2+D3UNtxXnHFFQwdOpRvv/2WK6+8strX/Mtf/sKtt95KixYtOPPMM3G73Xz11Vfs3bs3FKAOHDiQO+64A6fTySmnnBJ6bNy4cZxwwgmhiogvv/ySpUuXcsYZZ9CmTRu+/PJLdu3aRY8ePRr83kVEmqxy6w2Q1jZQ7drltFiPTKTWmkI8CoH4ZteuXYpHq6F4tOHc3sj2fFXlq0h4KSPWENu/CVQX7NmCHxuTKOZhPFzc8xLmnDuHDFfV/8BWSL5Gse2AOwaVr+r32nhlZmYydmjvqB4zIyMjdHlQfU2ZMoU33nijzGNHdOvOlAcfY9ZTjzB16lQuuugixo0bx3PPPdegYwXNmDGDGTNmkJubS9euXXn33Xdp1aoVQKg6YMKECZxxxhm43W46derEmWeeWWlvqurceuut7Nu3jzvvvJNff/2VY445hnfffZdu3bo1+D3Udpynn346WVlZbNiwgcsvv7za17zuuutISUnhoYceYvz48aSmppKdnc3tt98e2iY7O5vMzEyOOuqoUH+vgQMH4vf7Q/21IPDZ+OSTT3j88cfZv38/nTp14pFHHuGss86q93u2LIu8vLxab5+ZmVnnORMRiZly6w1wxCAYNgfSWsd2XCJ10JTi0R49evDMM88wbdo0xaNVaI7xaLhFu+1AhhbPFmkQZcTqwxj49/Pw/t3g9/CLzc5wk8/qBAdPD5nFTX1vqtBmoDybzYYzwR6qQo1K8tURg56v7kDla7q+rBstu90e9dUb69K7CuDll1+u8Fjnzp1xu90Ue/xs/PVg9cJV11zHveNvK7NtcNXYql5r+fLlFR7btm1bmWMFe3dddtllVY6zW7duvP3221U+X9lxKmO328nJySEnJ6fKbWpz+VpVx6tpnMEx/PLLL5U+l5OTwx133FHmscsvv7zaoNhut7Nnz54yj/Xq1atCT7QePXqwePHiasdWV1rRVESarB1rA4UAv20Emx0G3QOnjAWdQJI4E+/xaHmjRo1i1KhRZR5TPFpWQ+PRyZMnc//997N///7QY405Hg23YB4hUsnXim0HGl/qSAUWEk8a319QY1eyD969Bb77JwALbH7+bPaT2bILKy9+kz4dql85sjRX6eRrFNoOJMag7UBBqOerPmoSGeXXcXPYqz/xIfHLGIPf7y/zmM/nCwVeTqezzHOlAyytaCoiTUq59QZI7wDDX4BOJ8V6ZCIiEgVuX2TbDpROviYl2iN2nIZQgYXEE2XE6uLn1fDm1ZD3PT6bjfGmmMeNhwt6XMBL579EZlJmnV7OlWAnWK/XVBfc2q+2AxJh9nJV5glKvjZZfr+fnXlF2Er1K/N5POSXePlg1Q8UllpIWAGWiDRZ5dYboOsf4cK/QeohMR2WiIhET6QX3CqdbG3M/V5VYCHxQhmx2jAGvpwNH9wHlpcf7XYusvazxmHnsT8+xm39bquxzUBlSn+hJSVGvvzdFap89dewZfgc7PnaeL+wJb7ZyyVbVfnatNkcjjKLRVgOBzabneTUdLAa3xl5EZGwKrXeADYHDM6B/reozYCISDMT6Z6vzlKXF6rfq0jDKflak6I98M8xsGEhAO/Y/Fxt7adF5uF8OvwNfn/Y7+v90sEvyuRER72St3UVPCsW1Z6vJcGer/qoSWTYbTbsNhvWgV5NSr6KiEiTU269AVp0hOEvQscTYz0yERGJAbf3QNuBCBVxla6obcyVryLxQhmx6vz4b5h3Nez7Ea/Nzh2mkFnGyzlHncMrF7zCISkNu7wr+IUWjcW24ODZK6/f1LBl+BS41XagMSrfVD7eKfkaXyrr3Vodh6OaE1Shz7LmXUSaqOI8+NetofUG6H42nD8LUtRWReJbU4tHpfmKxWc50j1fS1fUZij5KtJgyohVxrLg86dg6RSwfHxvd3ChtY//2G08+IcHGXfSOOy2hp9hKl35Gg3BZK87ij1f89XztVEJXq7t8XhITk6O8WjCx2G3EfxYO8LwtymRVVnv1qoYv5+2mSkkJFT+HeJxl+A3Bo+l5KuINEGl1hvAngh/nAK/vwmicMWUSKQkJgYSOUVFRU0qHpXmq6ioCDj42Y4GTyj5qspXkXigjFh5hb/B/Jtg4/sAvGmzuNbaT3pGB5YPf4NTDj8lbIcKnqWKWuVrQvQX3DrYdkBf2I1BQkICKSkp7Nq1i8TExNBK8NFmWRYej4eSkpKwjMH4PZgDfY98Hjcl+Br8mlK1hs6fz+fD7/dhp+YqAcvvp6SkhISEBHw+Hz6PB8vhAGPwuEv4bfcufimy41flq4g0JcbAF8/CkvvB8kJmJ7j4JTi0T6xHJtJgDoeDzMxMfv31VwBSUlKi0oKtvHDHoxJ9sZ5DYwxFRUX8+uuvZGZmllmXINIO9nyNzDFLJ18zIlxIZVkWe/bsqXXyOjMzU3+zEneUfC3t+89h3jWQ/wtem50xppDnjJczup7B3y/8O61TW4f1cMH+LNGufI1u8lWVr42JzWajffv2bN26le+//z5m4zDGUFxcTHJycliC7d35bkoOfK7thUkkqPVARJWev7pcZmWz2bDZbFiWRX6JF1stqpSNschPCpwoKL+f3xh+KbLzY4mz3u9FRKTRKdoD/xwNGxYF7vc4D857CpIzYzoskXBq164dQCgBGwvhjkcl+hrLHGZmZoY+09ESvJrVGaHKV1cUK18LCwt54r1vSEnPrHHbksJ8xg7tTVaWWu9IfFFGDAJtBlY8Bh89AMbPVkcCF/jzWGuHqQOncvepd4elzUB5UW874AguuFX7XosNFUy+prn0UWssnE4n3bp1w+PxxGwMXq+XTz75hNNOOy0sl+e8NH8tKzbvBuBft5xCilOft0gKzt9xxx3H3z/biCsltcZ93EWFjBzYg8zMTPLy8vhg1Q8kp6bXuF9xYT6Xndiukv1seCybKl5FpGn5cVWgEGDfj+BwwpBpcMJ1ajMgTU6wIKBNmzZ4vd6YjCHc8ahEX2OYw8TExKhWvAa5I9x2oHRFbTR6vianpZOakRnx44jEijIUBbvgnRtg80cAvGa3uN6/h7S0tnx40WsM6jIoYoeO+oJbajsgB9jtdpKSkmJ2fIfDgc/nIykpKSyBks+ewM/5fhLsNlqmp6p6oY4syyIvL6/W26empuLz+UhMTMSXmIqrFtVYPm8g8Z+UlITT6aTQC1g1f/cV1nM/EZG4Um69AVp2gYtfhg69Yj0ykYhyOBwxSVwFjx3OeFSirznPodt7oO1AYuR7vmrBLZGGaxSNMmbNmkXnzp1JSkqiX79+rFq1qtrt33zzTY4++miSkpLIzs5m0aJF9Tvw1k9h9imw+SM8dgfXUMzlVgEndBlI7qjciCZeoVTP1yhVvrqinHw1xlDgDlS+RrpPjDRv6QcqqzNTEpt14jXYL6m2N8sKfBfk5eXx6II1PLNsU423RxesqVOiVkQal7rGXM1JzOLRor3w2qUH+rv64NhhcOMnSryKiEiVDla+Rqjnq6N0z1clXyW8mmM8GvOM2BtvvMHYsWOZPXs2/fr14/HHH2fIkCFs2LCBNm3aVNh+5cqVXHbZZUyfPp2hQ4fy6quvcsEFF/D111/Ts2fPWh/X9uWzsP45MBberCMYWLiNLzw+7jvtPnIG5OCwRz4h6opy5WtiqO1AdJKvRR4/1oF2kGlKvkoEBT9fTeWsbF0rUYNN54NJ1KRaXM5fvl9SUqou9RFp6uoaczUnsYpHARyvDQfHbnC44KwHoc9ItRkQEZFqeSLddiCx7j1f6/MbRpqf5hqPxjwj9uijj3L99ddz9dVXAzB79mwWLlzIiy++yMSJEyts/8QTT3DmmWcyfvx4AKZOncqSJUt4+umnmT17dq2P6/jyGciwQ68rSTx7Jvf/8Ck2bAzpOiQ8b6wWgl+USVFecOvnvcUsXrs94sfbVxxoOeCw26JW3StNX2X/qNvchfiL80mx7OzZs6fCPsF/2OtasdmQ/YILRCmJKiKNRV1jruYkVvEogK3wV+jSPdBmoF1Pfs4r5r8/5TX0LUmE+Xx+vvnNhuPbnSREqPJMIktzGP+a8xzuzC8Bqk++1ve3iGVZFOzLw1+cD4ApyWfPnqpPCjbkN0x6es3bStPSXOPRmCZfPR4Pq1evZtKkSaHH7HY7gwcP5vPPP690n88//5yxY8eWeWzIkCHMnz+/0u3dbjdutzt0f9++fQD8UpTA7t9PwHQaAt/+j7a0BWDNmjWVvk7Lli1D/713796a31wt9tv78zbcu7az/xc3a9b4In687Vt24971Pat2wao1/ynznMN1cMEcv7uw1serzX4ZLge5ublVjrUu7w8gLS2N3bt3k5ubS0JC7T/Ckfh/qv3qt5/X663zHJb+vDz7/hqcSSmh57bsKsS7Zx8/+/dw///bV2Y/T0kRNw3pDVBhv+o0dL+WLVtWOtba7rdv729lvruqUlJUwPfff8/+/fvZu3cvO3/aRlJKWi33S6zXfj/8YGP37t388MMPUTlePOxXel8gqvtpDpvXfsF9f3YFvlf27dtHRkZG6DmXy4XL5aqwT31iruYiGvEoVB2TfpvSn139cmC7F7av4aMNu3l4ycZKXyOS8VpN+0Z7v7ruG7P9vloaH+Ns5PuV3jfqnzXNYfzvt+LdWu9Xet+m8L3246YU1njKFlZV97upKpX9hvHn5WFZ8PzCFaRUcbVuQ3/DpKWlsWfPHrb7EkhNr/k3ZbzFa/Hy26C++ykerQMTQz///LMBzMqVK8s8Pn78eHPiiSdWuk9iYqJ59dVXyzw2a9Ys06ZNm0q3z8nJMYBuuummm2666aZbk7/l5OSELeZqLqIRjxqjmFQ33XTTTTfddGseN8WjFcW87UCkTZo0qUxlwp49e+jSpQtr166lRYsWMRyZ1Fd+fj7HHHMM3333nS5TiFOaw/im+Yt/msP4t2/fPnr27MnWrVtDbUeASqsMpHFQTNq06Hs0/mkO45/mMP5pDuOb4tHai2nytVWrVjgcDnbu3Fnm8Z07d9KuXbtK92nXrl2dtq+q3Lljx45lyqIlfuzfvx+AQw89VHMYpzSH8U3zF/80h/EvOG9ZWVm1msP6xFzNRTTiUVBM2tToezT+aQ7jn+Yw/mkO45vi0dqLzNJ4teR0OunTpw9Lly4NPWZZFkuXLqV///6V7tO/f/8y2wMsWbKkyu1FREREmrv6xFzNheJRERERkchrzvFozNsOjB07lhEjRtC3b19OPPFEHn/8cQoLC0Mrn/35z3/m0EMPZfr06QDcdtttDBgwgEceeYRzzjmH119/na+++ornnnsulm9DREREpFGrKeZqzhSPioiIiERec41HY558vfTSS9m1axf3338/O3bsoFevXixevJi2bdsC8MMPP2C3HyzQPemkk3j11Ve59957ufvuu+nWrRvz58+nZ8+etTqey+UiJydHPSjimOYw/mkO45vmL/5pDuNffeawppirOYt2PAr6O4x3mr/4pzmMf5rD+Kc5jG+KR2vPZowxsR6EiIiIiIiIiIiISFMT056vIiIiIiIiIiIiIk2Vkq8iIiIiIiIiIiIiEaDkq4iIiIiIiIiIiEgEKPkqIiIiIiIiIiIiEgFNMvk6a9YsOnfuTFJSEv369WPVqlXVbv/mm29y9NFHk5SURHZ2NosWLYrSSKUqdZnDOXPmcOqpp9KyZUtatmzJ4MGDa5xziby6/h0Gvf7669hsNi644ILIDlCqVdf5y8vLY/To0bRv3x6Xy8VRRx2l79IYq+scPv7443Tv3p3k5GQ6duzIHXfcQUlJSZRGK6V98sknnHvuuXTo0AGbzcb8+fNr3Gf58uUcf/zxuFwuunbtyssvvxzxcUrNFJPGN8Wj8U/xaPxTTBrfFI/GN8WkYWSamNdff904nU7z4osvmm+//dZcf/31JjMz0+zcubPS7VesWGEcDoeZOXOm+e6778y9995rEhMTzX//+98oj1yC6jqHl19+uZk1a5ZZs2aNWbdunRk5cqRp0aKF+emnn6I8cgmq6xwGbd261Rx66KHm1FNPNeeff350BisV1HX+3G636du3rzn77LPNZ599ZrZu3WqWL19ucnNzozxyCarrHM6dO9e4XC4zd+5cs3XrVvP++++b9u3bmzvuuCPKIxdjjFm0aJG55557zNtvv20A884771S7/ZYtW0xKSooZO3as+e6778xTTz1lHA6HWbx4cXQGLJVSTBrfFI/GP8Wj8U8xaXxTPBr/FJOGT5NLvp544olm9OjRoft+v9906NDBTJ8+vdLtL7nkEnPOOeeUeaxfv37mxhtvjOg4pWp1ncPyfD6fSU9PN6+88kqkhig1qM8c+nw+c9JJJ5nnn3/ejBgxQsFuDNV1/p599llzxBFHGI/HE60hSg3qOoejR482p59+epnHxo4da04++eSIjlNqVptA96677jLHHntsmccuvfRSM2TIkAiOTGqimDS+KR6Nf4pH459i0vimeLRpUUzaME2q7YDH42H16tUMHjw49Jjdbmfw4MF8/vnnle7z+eefl9keYMiQIVVuL5FVnzksr6ioCK/XS1ZWVqSGKdWo7xxOmTKFNm3acO2110ZjmFKF+szfu+++S//+/Rk9ejRt27alZ8+eTJs2Db/fH61hSyn1mcOTTjqJ1atXhy4F27JlC4sWLeLss8+OypilYRTLND6KSeOb4tH4p3g0/ikmjW+KR5snxTJVS4j1AMJp9+7d+P1+2rZtW+bxtm3bsn79+kr32bFjR6Xb79ixI2LjlKrVZw7LmzBhAh06dKjwRy/RUZ85/Oyzz3jhhRfIzc2NwgilOvWZvy1btvDRRx9xxRVXsGjRIjZt2sTNN9+M1+slJycnGsOWUuozh5dffjm7d+/mlFNOwRiDz+dj1KhR3H333dEYsjRQVbHM/v37KS4uJjk5OUYja74Uk8Y3xaPxT/Fo/FNMGt8UjzZPikmr1qQqX0VmzJjB66+/zjvvvENSUlKshyO1kJ+fz1VXXcWcOXNo1apVrIcj9WBZFm3atOG5556jT58+XHrppdxzzz3Mnj071kOTWlq+fDnTpk3jmWee4euvv+btt99m4cKFTJ06NdZDExGJO4pH44/i0aZBMWl8UzwqTVmTqnxt1aoVDoeDnTt3lnl8586dtGvXrtJ92rVrV6ftJbLqM4dBDz/8MDNmzODDDz/kd7/7XSSHKdWo6xxu3ryZbdu2ce6554YesywLgISEBDZs2MCRRx4Z2UFLSH3+Btu3b09iYiIOhyP0WI8ePdixYwcejwen0xnRMUtZ9ZnD++67j6uuuorrrrsOgOzsbAoLC7nhhhu45557sNt1rrYxqyqWycjIaNYVBrGkmDS+KR6Nf4pH459i0vimeLR5UkxatSb16XU6nfTp04elS5eGHrMsi6VLl9K/f/9K9+nfv3+Z7QGWLFlS5fYSWfWZQ4CZM2cydepUFi9eTN++faMxVKlCXefw6KOP5r///S+5ubmh23nnncegQYPIzc2lY8eO0Rx+s1efv8GTTz6ZTZs2hX6kAPzvf/+jffv2CnJjoD5zWFRUVCGgDf5wMcZEbrASFoplGh/FpPFN8Wj8Uzwa/xSTxjfFo82TYplqxHa9r/B7/fXXjcvlMi+//LL57rvvzA033GAyMzPNjh07jDHGXHXVVWbixImh7VesWGESEhLMww8/bNatW2dycnJMYmKi+e9//xurt9Ds1XUOZ8yYYZxOp5k3b57Zvn176Jafnx+rt9Ds1XUOy9PqsrFV1/n74YcfTHp6uhkzZozZsGGDWbBggWnTpo3561//Gqu30OzVdQ5zcnJMenq6ee2118yWLVvMBx98YI488khzySWXxOotNGv5+flmzZo1Zs2aNQYwjz76qFmzZo35/vvvjTHGTJw40Vx11VWh7bds2WJSUlLM+PHjzbp168ysWbOMw+EwixcvjtVbEKOYNN4pHo1/ikfjn2LS+KZ4NP4pJg2fJpd8NcaYp556yhx++OHG6XSaE0880XzxxReh5wYMGGBGjBhRZvt//OMf5qijjjJOp9Mce+yxZuHChVEesZRXlzns1KmTASrccnJyoj9wCanr32FpCnZjr67zt3LlStOvXz/jcrnMEUccYR544AHj8/miPGoprS5z6PV6zeTJk82RRx5pkpKSTMeOHc3NN99s9u7dG/2Bi1m2bFml/64F52zEiBFmwIABFfbp1auXcTqd5ogjjjAvvfRS1MctFSkmjW+KR+Of4tH4p5g0vikejW+KScPHZozqt0VERERERERERETCrUn1fBURERERERERERFpLJR8FREREREREREREYkAJV9FREREREREREREIkDJVxEREREREREREZEIUPJVREREREREREREJAKUfBURERERERERERGJACVfRURERERERERERCJAyVcRERERERERERGRCFDyVUSkFkaOHMkFF1wQuj9w4EBuv/32qI9j+fLl2Gw28vLyon5sEREREYktxaQiIvFHyVcRiVsjR47EZrNhs9lwOp107dqVKVOm4PP5In7st99+m6lTp9Zq22gHp507dw79f0lJSSE7O5vnn38+KscWERERaW4Uk1ZOMamISICSryIS184880y2b9/Oxo0bufPOO5k8eTIPPfRQpdt6PJ6wHTcrK4v09PSwvV64TZkyhe3bt7N27VquvPJKrr/+et57771YD0tERESkSVJMWjnFpCIiSr6KSJxzuVy0a9eOTp06cdNNNzF48GDeffdd4OBlWQ888AAdOnSge/fuAPz4449ccsklZGZmkpWVxfnnn8+2bdtCr+n3+xk7diyZmZkccsgh3HXXXRhjyhy3/CVebrebCRMm0LFjR1wuF127duWFF15g27ZtDBo0CICWLVtis9kYOXIkAJZlMX36dLp06UJycjLHHXcc8+bNK3OcRYsWcdRRR5GcnMygQYPKjLM66enptGvXjiOOOIIJEyaQlZXFkiVL6vB/VkRERERqSzFp5RSTiogo+SoiTUxycnKZaoKlS5eyYcMGlixZwoIFC/B6vQwZMoT09HQ+/fRTVqxYQVpaGmeeeWZov0ceeYSXX36ZF198kc8++4w9e/bwzjvvVHvcP//5z7z22ms8+eSTrFu3jr/97W+kpaXRsWNH3nrrLQA2bNjA9u3beeKJJwCYPn06/+///T9mz57Nt99+yx133MGVV17Jxx9/DAQC8mHDhnHuueeSm5vLddddx8SJE+v0/8OyLN566y327t2L0+ms074iIiIiUj+KSctSTCoizZoREYlTI0aMMOeff74xxhjLssySJUuMy+Uy48aNCz3ftm1b43a7Q/v83//9n+nevbuxLCv0mNvtNsnJyeb99983xhjTvn17M3PmzNDzXq/XHHbYYaFjGWPMgAEDzG233WaMMWbDhg0GMEuWLKl0nMuWLTOA2bt3b+ixkpISk5KSYlauXFlm22uvvdZcdtllxhhjJk2aZI455pgyz0+YMKHCa5XXqVMn43Q6TWpqqklISDCAycrKMhs3bqxyHxERERGpH8WklVNMKiISkBC7tK+ISMMtWLCAtLQ0vF4vlmVx+eWXM3ny5NDz2dnZZc6uf/PNN2zatKlCb6ySkhI2b97Mvn372L59O/369Qs9l5CQQN++fStc5hWUm5uLw+FgwIABtR73pk2bKCoq4o9//GOZxz0eD7179wZg3bp1ZcYB0L9//1q9/vjx4xk5ciTbt29n/Pjx3HzzzXTt2rXW4xMRERGR2lNMWjnFpCIioOSriMS1QYMG8eyzz+J0OunQoQMJCWW/1lJTU8vcLygooE+fPsydO7fCa7Vu3bpeY0hOTq7zPgUFBQAsXLiQQw89tMxzLperXuMorVWrVnTt2pWuXbvy5ptvkp2dTd++fTnmmGMa/NoiIiIiUpZi0sopJhURUc9XEYlzqampdO3alcMPP7xCkFuZ448/no0bN9KmTZtQIBi8tWjRghYtWtC+fXu+/PLL0D4+n4/Vq1dX+ZrZ2dlYlhXqi1VesMrB7/eHHjvmmGNwuVz88MMPFcbRsWNHAHr06MGqVavKvNYXX3xR43ssr2PHjlx66aVMmjSpzvuKiIiISM0Uk9ZMMamINFdKvopIs3LFFVfQqlUrzj//fD799FO2bt3K8uXLufXWW/npp58AuO2225gxYwbz589n/fr13HzzzeTl5VX5mp07d2bEiBFcc801zJ8/P/Sa//jHPwDo1KkTNpuNBQsWsGvXLgoKCkhPT2fcuHHccccdvPLKK2zevJmvv/6ap556ildeeQWAUaNGsXHjRsaPH8+GDRt49dVXefnll+v1vm+77Tb+9a9/8dVXX9VrfxEREREJH8WkiklFpPlQ8lVEmpWUlBQ++eQTDj/8cIYNG0aPHj249tprKSkpISMjA4A777yTq666ihEjRtC/f3/S09O58MILq33dZ599luHDh3PzzTdz9NFHc/3111NYWAjAoYceyl/+8hcmTpxI27ZtGTNmDABTp07lvvvuY/r06fTo0YMzzzyThQsX0qVLFwAOP/xw3nrrLebPn89xxx3H7NmzmTZtWr3e9zHHHMMZZ5zB/fffX6/9RURERCR8FJMqJhWR5sNmqurWLSIiIiIiIiIiIiL1pspXERERERERERERkQhQ8lVEREREREREREQkApR8FREREREREREREYkAJV9FREREREREREREIkDJVxEREREREREREZEIUPJVREREREREREREJAKUfBURERERERERERGJACVfRURERERERERERCJAyVcRERERERERERGRCFDyVURERERERERERCQClHwVERERERERERERiYD/D1d9YyWfqP7pAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1600x1200 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# code from https://github.com/papousek/duolingo-halflife-regression/blob/master/evaluation.py\n",
    "def load_brier(predictions, real, bins=20):\n",
    "    counts = np.zeros(bins)\n",
    "    correct = np.zeros(bins)\n",
    "    prediction = np.zeros(bins)\n",
    "    for p, r in zip(predictions, real):\n",
    "        bin = min(int(p * bins), bins - 1)\n",
    "        counts[bin] += 1\n",
    "        correct[bin] += r\n",
    "        prediction[bin] += p\n",
    "    np.seterr(invalid='ignore')\n",
    "    prediction_means = prediction / counts\n",
    "    prediction_means[np.isnan(prediction_means)] = ((np.arange(bins) + 0.5) / bins)[np.isnan(prediction_means)]\n",
    "    correct_means = correct / counts\n",
    "    correct_means[np.isnan(correct_means)] = 0\n",
    "    size = len(predictions)\n",
    "    answer_mean = sum(correct) / size\n",
    "    return {\n",
    "        \"reliability\": sum(counts * (correct_means - prediction_means) ** 2) / size,\n",
    "        \"resolution\": sum(counts * (correct_means - answer_mean) ** 2) / size,\n",
    "        \"uncertainty\": answer_mean * (1 - answer_mean),\n",
    "        \"detail\": {\n",
    "            \"bin_count\": bins,\n",
    "            \"bin_counts\": list(counts),\n",
    "            \"bin_prediction_means\": list(prediction_means),\n",
    "            \"bin_correct_means\": list(correct_means),\n",
    "        }\n",
    "    }\n",
    "\n",
    "\n",
    "def plot_brier(predictions, real, bins=20):\n",
    "    brier = load_brier(predictions, real, bins=bins)\n",
    "    bin_prediction_means = brier['detail']['bin_prediction_means']\n",
    "    bin_correct_means = brier['detail']['bin_correct_means']\n",
    "    bin_counts = brier['detail']['bin_counts']\n",
    "    r2 = r2_score(bin_correct_means, bin_prediction_means, sample_weight=bin_counts)\n",
    "    rmse = mean_squared_error(bin_correct_means, bin_prediction_means, sample_weight=bin_counts, squared=False)\n",
    "    print(f\"R-squared: {r2:.4f}\")\n",
    "    print(f\"RMSE: {rmse:.4f}\")\n",
    "    ax = plt.gca()\n",
    "    ax.set_xlim([0, 1])\n",
    "    ax.set_ylim([0, 1])\n",
    "    plt.grid(True)\n",
    "    fit_wls = sm.WLS(bin_correct_means, sm.add_constant(bin_prediction_means), weights=bin_counts).fit()\n",
    "    print(fit_wls.params)\n",
    "    y_regression = [fit_wls.params[0] + fit_wls.params[1]*x for x in bin_prediction_means]\n",
    "    plt.plot(bin_prediction_means, y_regression, label='Weighted Least Squares Regression', color=\"green\")\n",
    "    plt.plot(bin_prediction_means, bin_correct_means, label='Actual Calibration', color=\"#1f77b4\")\n",
    "    plt.plot((0, 1), (0, 1), label='Perfect Calibration', color=\"#ff7f0e\")\n",
    "    bin_count = brier['detail']['bin_count']\n",
    "    counts = np.array(bin_counts)\n",
    "    bins = (np.arange(bin_count) + 0.5) / bin_count\n",
    "    plt.legend(loc='upper center')\n",
    "    plt.xlabel('Predicted R')\n",
    "    plt.ylabel('Actual R')\n",
    "    plt.twinx()\n",
    "    plt.ylabel('Number of reviews')\n",
    "    plt.bar(bins, counts, width=(0.8 / bin_count), ec='k', lw=.2, alpha=0.5, label='Number of reviews')\n",
    "    plt.legend(loc='lower center')\n",
    "\n",
    "\n",
    "plot_brier(dataset['p'], dataset['y'], bins=40)\n",
    "plt.show()\n",
    "plt.figure(figsize=(16, 12))\n",
    "for last_rating in (\"1\",\"2\",\"3\",\"4\"):\n",
    "    plt.subplot(2, 2, int(last_rating))\n",
    "    print(f\"\\nLast rating: {last_rating}\")\n",
    "    plot_brier(dataset[dataset['r_history'].str.endswith(last_rating)]['p'], dataset[dataset['r_history'].str.endswith(last_rating)]['y'], bins=40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def to_percent(temp, position):\n",
    "    return '%1.0f' % (100 * temp) + '%'\n",
    "\n",
    "fig = plt.figure(1)\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax2 = ax1.twinx()\n",
    "lns = []\n",
    "\n",
    "stability_calibration = pd.DataFrame(columns=['stability', 'predicted_retention', 'actual_retention'])\n",
    "stability_calibration = dataset[['stability', 'p', 'y']].copy()\n",
    "stability_calibration['bin'] = stability_calibration['stability'].map(lambda x: math.pow(1.2, math.floor(math.log(x, 1.2))))\n",
    "stability_group = stability_calibration.groupby('bin').count()\n",
    "\n",
    "lns1 = ax1.bar(x=stability_group.index, height=stability_group['y'], width=stability_group.index / 5.5,\n",
    "                ec='k', lw=.2, label='Number of predictions', alpha=0.5)\n",
    "ax1.set_ylabel(\"Number of predictions\")\n",
    "ax1.set_xlabel(\"Stability (days)\")\n",
    "ax1.semilogx()\n",
    "lns.append(lns1)\n",
    "\n",
    "stability_group = stability_calibration.groupby(by='bin').agg('mean')\n",
    "lns2 = ax2.plot(stability_group['y'], label='Actual retention')\n",
    "lns3 = ax2.plot(stability_group['p'], label='Predicted retention')\n",
    "ax2.set_ylabel(\"Retention\")\n",
    "ax2.set_ylim(0, 1)\n",
    "lns.append(lns2[0])\n",
    "lns.append(lns3[0])\n",
    "\n",
    "labs = [l.get_label() for l in lns]\n",
    "ax2.legend(lns, labs, loc='lower right')\n",
    "plt.grid(linestyle='--')\n",
    "plt.gca().yaxis.set_major_formatter(ticker.FuncFormatter(to_percent))\n",
    "plt.gca().xaxis.set_major_formatter(ticker.FormatStrFormatter('%d'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(1)\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax2 = ax1.twinx()\n",
    "lns = []\n",
    "\n",
    "difficulty_calibration = pd.DataFrame(columns=['difficulty', 'predicted_retention', 'actual_retention'])\n",
    "difficulty_calibration = dataset[['difficulty', 'p', 'y']].copy()\n",
    "difficulty_calibration['bin'] = difficulty_calibration['difficulty'].map(round)\n",
    "difficulty_group = difficulty_calibration.groupby('bin').count()\n",
    "\n",
    "lns1 = ax1.bar(x=difficulty_group.index, height=difficulty_group['y'],\n",
    "                ec='k', lw=.2, label='Number of predictions', alpha=0.5)\n",
    "ax1.set_ylabel(\"Number of predictions\")\n",
    "ax1.set_xlabel(\"Difficulty\")\n",
    "lns.append(lns1)\n",
    "\n",
    "difficulty_group = difficulty_calibration.groupby(by='bin').agg('mean')\n",
    "lns2 = ax2.plot(difficulty_group['y'], label='Actual retention')\n",
    "lns3 = ax2.plot(difficulty_group['p'], label='Predicted retention')\n",
    "ax2.set_ylabel(\"Retention\")\n",
    "ax2.set_ylim(0, 1)\n",
    "lns.append(lns2[0])\n",
    "lns.append(lns3[0])\n",
    "\n",
    "labs = [l.get_label() for l in lns]\n",
    "ax2.legend(lns, labs, loc='lower right')\n",
    "plt.grid(linestyle='--')\n",
    "plt.gca().yaxis.set_major_formatter(ticker.FuncFormatter(to_percent))\n",
    "plt.gca().xaxis.set_major_formatter(ticker.FormatStrFormatter('%d'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_34a42_row0_col0, #T_34a42_row0_col1, #T_34a42_row0_col2, #T_34a42_row0_col3, #T_34a42_row0_col4, #T_34a42_row0_col5, #T_34a42_row1_col0, #T_34a42_row1_col1, #T_34a42_row1_col2, #T_34a42_row1_col3, #T_34a42_row1_col4, #T_34a42_row2_col0, #T_34a42_row2_col1, #T_34a42_row2_col2, #T_34a42_row2_col3, #T_34a42_row3_col0, #T_34a42_row3_col1, #T_34a42_row3_col2, #T_34a42_row4_col0, #T_34a42_row4_col1, #T_34a42_row5_col1, #T_34a42_row6_col1, #T_34a42_row7_col1, #T_34a42_row8_col1, #T_34a42_row9_col7, #T_34a42_row10_col7, #T_34a42_row11_col7, #T_34a42_row12_col6, #T_34a42_row12_col7, #T_34a42_row13_col0, #T_34a42_row13_col4, #T_34a42_row13_col5, #T_34a42_row13_col6, #T_34a42_row13_col7, #T_34a42_row14_col0, #T_34a42_row14_col3, #T_34a42_row14_col4, #T_34a42_row14_col5, #T_34a42_row14_col6, #T_34a42_row14_col7 {\n",
       "  background-color: #000000;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_34a42_row0_col6, #T_34a42_row10_col4, #T_34a42_row10_col6 {\n",
       "  background-color: #ffbdbd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row0_col7, #T_34a42_row2_col4, #T_34a42_row6_col6 {\n",
       "  background-color: #ffc9c9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row1_col5 {\n",
       "  background-color: #9191ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_34a42_row1_col6 {\n",
       "  background-color: #ff8585;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_34a42_row1_col7, #T_34a42_row4_col7, #T_34a42_row12_col4 {\n",
       "  background-color: #f5f5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row2_col5, #T_34a42_row3_col7 {\n",
       "  background-color: #fff9f9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row2_col6, #T_34a42_row4_col6, #T_34a42_row11_col1 {\n",
       "  background-color: #cdcdff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row2_col7, #T_34a42_row7_col2, #T_34a42_row8_col7, #T_34a42_row12_col0 {\n",
       "  background-color: #fdfdff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row3_col3, #T_34a42_row8_col0, #T_34a42_row9_col0 {\n",
       "  background-color: #c9c9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row3_col4 {\n",
       "  background-color: #ffdddd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row3_col5 {\n",
       "  background-color: #c1c1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row3_col6, #T_34a42_row5_col3, #T_34a42_row9_col1, #T_34a42_row10_col3 {\n",
       "  background-color: #f9f9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row4_col2 {\n",
       "  background-color: #e5e5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row4_col3 {\n",
       "  background-color: #f1f1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row4_col4, #T_34a42_row6_col5, #T_34a42_row8_col3, #T_34a42_row10_col2 {\n",
       "  background-color: #fffdfd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row4_col5, #T_34a42_row6_col3, #T_34a42_row7_col0 {\n",
       "  background-color: #d1d1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row5_col0 {\n",
       "  background-color: #ddddff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row5_col2, #T_34a42_row8_col2 {\n",
       "  background-color: #d9d9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row5_col4 {\n",
       "  background-color: #d5d5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row5_col5 {\n",
       "  background-color: #ffd9d9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row5_col6, #T_34a42_row6_col0 {\n",
       "  background-color: #e1e1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row5_col7, #T_34a42_row10_col5 {\n",
       "  background-color: #ffd1d1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row6_col2 {\n",
       "  background-color: #c5c5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row6_col4 {\n",
       "  background-color: #ff9999;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row6_col7 {\n",
       "  background-color: #ff9595;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row7_col3, #T_34a42_row9_col2, #T_34a42_row11_col0 {\n",
       "  background-color: #ffeded;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row7_col4 {\n",
       "  background-color: #ffc1c1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row7_col5 {\n",
       "  background-color: #fff5f5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row7_col6 {\n",
       "  background-color: #ff9d9d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row7_col7 {\n",
       "  background-color: #ffc5c5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row8_col4 {\n",
       "  background-color: #ffa9a9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row8_col5 {\n",
       "  background-color: #ff9191;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row8_col6, #T_34a42_row11_col4 {\n",
       "  background-color: #ffa1a1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row9_col3, #T_34a42_row12_col5 {\n",
       "  background-color: #ffe5e5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row9_col4 {\n",
       "  background-color: #ffa5a5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row9_col5 {\n",
       "  background-color: #ffadad;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row9_col6 {\n",
       "  background-color: #ff6969;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_34a42_row10_col0, #T_34a42_row14_col1 {\n",
       "  background-color: #b5b5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row10_col1 {\n",
       "  background-color: #bdbdff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row11_col2 {\n",
       "  background-color: #ededff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row11_col3 {\n",
       "  background-color: #ffb5b5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row11_col5 {\n",
       "  background-color: #ffcdcd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row11_col6 {\n",
       "  background-color: #ff8d8d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row12_col1, #T_34a42_row13_col1 {\n",
       "  background-color: #9d9dff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_34a42_row12_col2 {\n",
       "  background-color: #a9a9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row12_col3 {\n",
       "  background-color: #ffd5d5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34a42_row13_col2 {\n",
       "  background-color: #9999ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_34a42_row13_col3 {\n",
       "  background-color: #6969ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_34a42_row14_col2 {\n",
       "  background-color: #8989ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_34a42\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >d_bin</th>\n",
       "      <th id=\"T_34a42_level0_col0\" class=\"col_heading level0 col0\" >3</th>\n",
       "      <th id=\"T_34a42_level0_col1\" class=\"col_heading level0 col1\" >4</th>\n",
       "      <th id=\"T_34a42_level0_col2\" class=\"col_heading level0 col2\" >5</th>\n",
       "      <th id=\"T_34a42_level0_col3\" class=\"col_heading level0 col3\" >6</th>\n",
       "      <th id=\"T_34a42_level0_col4\" class=\"col_heading level0 col4\" >7</th>\n",
       "      <th id=\"T_34a42_level0_col5\" class=\"col_heading level0 col5\" >8</th>\n",
       "      <th id=\"T_34a42_level0_col6\" class=\"col_heading level0 col6\" >9</th>\n",
       "      <th id=\"T_34a42_level0_col7\" class=\"col_heading level0 col7\" >10</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >s_bin</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "      <th class=\"blank col7\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_34a42_level0_row0\" class=\"row_heading level0 row0\" >1.400000</th>\n",
       "      <td id=\"T_34a42_row0_col0\" class=\"data row0 col0\" ></td>\n",
       "      <td id=\"T_34a42_row0_col1\" class=\"data row0 col1\" ></td>\n",
       "      <td id=\"T_34a42_row0_col2\" class=\"data row0 col2\" ></td>\n",
       "      <td id=\"T_34a42_row0_col3\" class=\"data row0 col3\" ></td>\n",
       "      <td id=\"T_34a42_row0_col4\" class=\"data row0 col4\" ></td>\n",
       "      <td id=\"T_34a42_row0_col5\" class=\"data row0 col5\" ></td>\n",
       "      <td id=\"T_34a42_row0_col6\" class=\"data row0 col6\" >2.58%</td>\n",
       "      <td id=\"T_34a42_row0_col7\" class=\"data row0 col7\" >2.08%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34a42_level0_row1\" class=\"row_heading level0 row1\" >1.960000</th>\n",
       "      <td id=\"T_34a42_row1_col0\" class=\"data row1 col0\" ></td>\n",
       "      <td id=\"T_34a42_row1_col1\" class=\"data row1 col1\" ></td>\n",
       "      <td id=\"T_34a42_row1_col2\" class=\"data row1 col2\" ></td>\n",
       "      <td id=\"T_34a42_row1_col3\" class=\"data row1 col3\" ></td>\n",
       "      <td id=\"T_34a42_row1_col4\" class=\"data row1 col4\" ></td>\n",
       "      <td id=\"T_34a42_row1_col5\" class=\"data row1 col5\" >-4.25%</td>\n",
       "      <td id=\"T_34a42_row1_col6\" class=\"data row1 col6\" >4.78%</td>\n",
       "      <td id=\"T_34a42_row1_col7\" class=\"data row1 col7\" >-0.40%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34a42_level0_row2\" class=\"row_heading level0 row2\" >2.740000</th>\n",
       "      <td id=\"T_34a42_row2_col0\" class=\"data row2 col0\" ></td>\n",
       "      <td id=\"T_34a42_row2_col1\" class=\"data row2 col1\" ></td>\n",
       "      <td id=\"T_34a42_row2_col2\" class=\"data row2 col2\" ></td>\n",
       "      <td id=\"T_34a42_row2_col3\" class=\"data row2 col3\" ></td>\n",
       "      <td id=\"T_34a42_row2_col4\" class=\"data row2 col4\" >2.06%</td>\n",
       "      <td id=\"T_34a42_row2_col5\" class=\"data row2 col5\" >0.27%</td>\n",
       "      <td id=\"T_34a42_row2_col6\" class=\"data row2 col6\" >-1.90%</td>\n",
       "      <td id=\"T_34a42_row2_col7\" class=\"data row2 col7\" >-0.04%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34a42_level0_row3\" class=\"row_heading level0 row3\" >3.840000</th>\n",
       "      <td id=\"T_34a42_row3_col0\" class=\"data row3 col0\" ></td>\n",
       "      <td id=\"T_34a42_row3_col1\" class=\"data row3 col1\" ></td>\n",
       "      <td id=\"T_34a42_row3_col2\" class=\"data row3 col2\" ></td>\n",
       "      <td id=\"T_34a42_row3_col3\" class=\"data row3 col3\" >-2.15%</td>\n",
       "      <td id=\"T_34a42_row3_col4\" class=\"data row3 col4\" >1.36%</td>\n",
       "      <td id=\"T_34a42_row3_col5\" class=\"data row3 col5\" >-2.37%</td>\n",
       "      <td id=\"T_34a42_row3_col6\" class=\"data row3 col6\" >-0.20%</td>\n",
       "      <td id=\"T_34a42_row3_col7\" class=\"data row3 col7\" >0.24%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34a42_level0_row4\" class=\"row_heading level0 row4\" >5.380000</th>\n",
       "      <td id=\"T_34a42_row4_col0\" class=\"data row4 col0\" ></td>\n",
       "      <td id=\"T_34a42_row4_col1\" class=\"data row4 col1\" ></td>\n",
       "      <td id=\"T_34a42_row4_col2\" class=\"data row4 col2\" >-1.03%</td>\n",
       "      <td id=\"T_34a42_row4_col3\" class=\"data row4 col3\" >-0.61%</td>\n",
       "      <td id=\"T_34a42_row4_col4\" class=\"data row4 col4\" >0.13%</td>\n",
       "      <td id=\"T_34a42_row4_col5\" class=\"data row4 col5\" >-1.75%</td>\n",
       "      <td id=\"T_34a42_row4_col6\" class=\"data row4 col6\" >-1.93%</td>\n",
       "      <td id=\"T_34a42_row4_col7\" class=\"data row4 col7\" >-0.34%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34a42_level0_row5\" class=\"row_heading level0 row5\" >7.530000</th>\n",
       "      <td id=\"T_34a42_row5_col0\" class=\"data row5 col0\" >-1.32%</td>\n",
       "      <td id=\"T_34a42_row5_col1\" class=\"data row5 col1\" ></td>\n",
       "      <td id=\"T_34a42_row5_col2\" class=\"data row5 col2\" >-1.44%</td>\n",
       "      <td id=\"T_34a42_row5_col3\" class=\"data row5 col3\" >-0.18%</td>\n",
       "      <td id=\"T_34a42_row5_col4\" class=\"data row5 col4\" >-1.58%</td>\n",
       "      <td id=\"T_34a42_row5_col5\" class=\"data row5 col5\" >1.52%</td>\n",
       "      <td id=\"T_34a42_row5_col6\" class=\"data row5 col6\" >-1.13%</td>\n",
       "      <td id=\"T_34a42_row5_col7\" class=\"data row5 col7\" >1.72%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34a42_level0_row6\" class=\"row_heading level0 row6\" >10.540000</th>\n",
       "      <td id=\"T_34a42_row6_col0\" class=\"data row6 col0\" >-1.19%</td>\n",
       "      <td id=\"T_34a42_row6_col1\" class=\"data row6 col1\" ></td>\n",
       "      <td id=\"T_34a42_row6_col2\" class=\"data row6 col2\" >-2.22%</td>\n",
       "      <td id=\"T_34a42_row6_col3\" class=\"data row6 col3\" >-1.86%</td>\n",
       "      <td id=\"T_34a42_row6_col4\" class=\"data row6 col4\" >4.00%</td>\n",
       "      <td id=\"T_34a42_row6_col5\" class=\"data row6 col5\" >0.14%</td>\n",
       "      <td id=\"T_34a42_row6_col6\" class=\"data row6 col6\" >2.12%</td>\n",
       "      <td id=\"T_34a42_row6_col7\" class=\"data row6 col7\" >4.19%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34a42_level0_row7\" class=\"row_heading level0 row7\" >14.760000</th>\n",
       "      <td id=\"T_34a42_row7_col0\" class=\"data row7 col0\" >-1.87%</td>\n",
       "      <td id=\"T_34a42_row7_col1\" class=\"data row7 col1\" ></td>\n",
       "      <td id=\"T_34a42_row7_col2\" class=\"data row7 col2\" >-0.12%</td>\n",
       "      <td id=\"T_34a42_row7_col3\" class=\"data row7 col3\" >0.63%</td>\n",
       "      <td id=\"T_34a42_row7_col4\" class=\"data row7 col4\" >2.38%</td>\n",
       "      <td id=\"T_34a42_row7_col5\" class=\"data row7 col5\" >0.31%</td>\n",
       "      <td id=\"T_34a42_row7_col6\" class=\"data row7 col6\" >3.76%</td>\n",
       "      <td id=\"T_34a42_row7_col7\" class=\"data row7 col7\" >2.20%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34a42_level0_row8\" class=\"row_heading level0 row8\" >20.660000</th>\n",
       "      <td id=\"T_34a42_row8_col0\" class=\"data row8 col0\" >-2.14%</td>\n",
       "      <td id=\"T_34a42_row8_col1\" class=\"data row8 col1\" ></td>\n",
       "      <td id=\"T_34a42_row8_col2\" class=\"data row8 col2\" >-1.54%</td>\n",
       "      <td id=\"T_34a42_row8_col3\" class=\"data row8 col3\" >0.13%</td>\n",
       "      <td id=\"T_34a42_row8_col4\" class=\"data row8 col4\" >3.35%</td>\n",
       "      <td id=\"T_34a42_row8_col5\" class=\"data row8 col5\" >4.37%</td>\n",
       "      <td id=\"T_34a42_row8_col6\" class=\"data row8 col6\" >3.60%</td>\n",
       "      <td id=\"T_34a42_row8_col7\" class=\"data row8 col7\" >-0.06%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34a42_level0_row9\" class=\"row_heading level0 row9\" >28.930000</th>\n",
       "      <td id=\"T_34a42_row9_col0\" class=\"data row9 col0\" >-2.13%</td>\n",
       "      <td id=\"T_34a42_row9_col1\" class=\"data row9 col1\" >-0.23%</td>\n",
       "      <td id=\"T_34a42_row9_col2\" class=\"data row9 col2\" >0.72%</td>\n",
       "      <td id=\"T_34a42_row9_col3\" class=\"data row9 col3\" >1.03%</td>\n",
       "      <td id=\"T_34a42_row9_col4\" class=\"data row9 col4\" >3.51%</td>\n",
       "      <td id=\"T_34a42_row9_col5\" class=\"data row9 col5\" >3.17%</td>\n",
       "      <td id=\"T_34a42_row9_col6\" class=\"data row9 col6\" >5.80%</td>\n",
       "      <td id=\"T_34a42_row9_col7\" class=\"data row9 col7\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34a42_level0_row10\" class=\"row_heading level0 row10\" >40.500000</th>\n",
       "      <td id=\"T_34a42_row10_col0\" class=\"data row10 col0\" >-2.83%</td>\n",
       "      <td id=\"T_34a42_row10_col1\" class=\"data row10 col1\" >-2.59%</td>\n",
       "      <td id=\"T_34a42_row10_col2\" class=\"data row10 col2\" >0.06%</td>\n",
       "      <td id=\"T_34a42_row10_col3\" class=\"data row10 col3\" >-0.25%</td>\n",
       "      <td id=\"T_34a42_row10_col4\" class=\"data row10 col4\" >2.61%</td>\n",
       "      <td id=\"T_34a42_row10_col5\" class=\"data row10 col5\" >1.75%</td>\n",
       "      <td id=\"T_34a42_row10_col6\" class=\"data row10 col6\" >2.56%</td>\n",
       "      <td id=\"T_34a42_row10_col7\" class=\"data row10 col7\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34a42_level0_row11\" class=\"row_heading level0 row11\" >56.690000</th>\n",
       "      <td id=\"T_34a42_row11_col0\" class=\"data row11 col0\" >0.65%</td>\n",
       "      <td id=\"T_34a42_row11_col1\" class=\"data row11 col1\" >-1.95%</td>\n",
       "      <td id=\"T_34a42_row11_col2\" class=\"data row11 col2\" >-0.69%</td>\n",
       "      <td id=\"T_34a42_row11_col3\" class=\"data row11 col3\" >2.86%</td>\n",
       "      <td id=\"T_34a42_row11_col4\" class=\"data row11 col4\" >3.69%</td>\n",
       "      <td id=\"T_34a42_row11_col5\" class=\"data row11 col5\" >2.00%</td>\n",
       "      <td id=\"T_34a42_row11_col6\" class=\"data row11 col6\" >4.38%</td>\n",
       "      <td id=\"T_34a42_row11_col7\" class=\"data row11 col7\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34a42_level0_row12\" class=\"row_heading level0 row12\" >79.370000</th>\n",
       "      <td id=\"T_34a42_row12_col0\" class=\"data row12 col0\" >-0.08%</td>\n",
       "      <td id=\"T_34a42_row12_col1\" class=\"data row12 col1\" >-3.75%</td>\n",
       "      <td id=\"T_34a42_row12_col2\" class=\"data row12 col2\" >-3.29%</td>\n",
       "      <td id=\"T_34a42_row12_col3\" class=\"data row12 col3\" >1.72%</td>\n",
       "      <td id=\"T_34a42_row12_col4\" class=\"data row12 col4\" >-0.44%</td>\n",
       "      <td id=\"T_34a42_row12_col5\" class=\"data row12 col5\" >0.94%</td>\n",
       "      <td id=\"T_34a42_row12_col6\" class=\"data row12 col6\" ></td>\n",
       "      <td id=\"T_34a42_row12_col7\" class=\"data row12 col7\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34a42_level0_row13\" class=\"row_heading level0 row13\" >111.120000</th>\n",
       "      <td id=\"T_34a42_row13_col0\" class=\"data row13 col0\" ></td>\n",
       "      <td id=\"T_34a42_row13_col1\" class=\"data row13 col1\" >-3.85%</td>\n",
       "      <td id=\"T_34a42_row13_col2\" class=\"data row13 col2\" >-4.01%</td>\n",
       "      <td id=\"T_34a42_row13_col3\" class=\"data row13 col3\" >-5.92%</td>\n",
       "      <td id=\"T_34a42_row13_col4\" class=\"data row13 col4\" ></td>\n",
       "      <td id=\"T_34a42_row13_col5\" class=\"data row13 col5\" ></td>\n",
       "      <td id=\"T_34a42_row13_col6\" class=\"data row13 col6\" ></td>\n",
       "      <td id=\"T_34a42_row13_col7\" class=\"data row13 col7\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34a42_level0_row14\" class=\"row_heading level0 row14\" >155.570000</th>\n",
       "      <td id=\"T_34a42_row14_col0\" class=\"data row14 col0\" ></td>\n",
       "      <td id=\"T_34a42_row14_col1\" class=\"data row14 col1\" >-2.82%</td>\n",
       "      <td id=\"T_34a42_row14_col2\" class=\"data row14 col2\" >-4.58%</td>\n",
       "      <td id=\"T_34a42_row14_col3\" class=\"data row14 col3\" ></td>\n",
       "      <td id=\"T_34a42_row14_col4\" class=\"data row14 col4\" ></td>\n",
       "      <td id=\"T_34a42_row14_col5\" class=\"data row14 col5\" ></td>\n",
       "      <td id=\"T_34a42_row14_col6\" class=\"data row14 col6\" ></td>\n",
       "      <td id=\"T_34a42_row14_col7\" class=\"data row14 col7\" ></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x2b16e0850>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "B_W_Metric_raw = dataset[['difficulty', 'stability', 'p', 'y']].copy()\n",
    "B_W_Metric_raw['s_bin'] = B_W_Metric_raw['stability'].map(lambda x: round(math.pow(1.4, math.floor(math.log(x, 1.4))), 2))\n",
    "B_W_Metric_raw['d_bin'] = B_W_Metric_raw['difficulty'].map(lambda x: int(round(x)))\n",
    "B_W_Metric = B_W_Metric_raw.groupby(by=['s_bin', 'd_bin']).agg('mean').reset_index()\n",
    "B_W_Metric_count = B_W_Metric_raw.groupby(by=['s_bin', 'd_bin']).agg('count').reset_index()\n",
    "B_W_Metric['B-W'] = B_W_Metric['p'] - B_W_Metric['y']\n",
    "n = len(dataset)\n",
    "bins = len(B_W_Metric)\n",
    "B_W_Metric_pivot = B_W_Metric[B_W_Metric_count['p'] > max(50, n / (3 * bins))].pivot(index=\"s_bin\", columns='d_bin', values='B-W')\n",
    "B_W_Metric_pivot.apply(pd.to_numeric).style.background_gradient(cmap='seismic', axis=None, vmin=-0.2, vmax=0.2).format(\"{:.2%}\", na_rep='')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R_Metric:  0.04091568031871751\n",
      "R-squared: -6.8749\n",
      "RMSE: 0.1527\n",
      "[0.68927589 0.25115013]\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Universal Metric of FSRS: 0.0106\n",
      "Universal Metric of SM2: 0.0789\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAi4AAAIjCAYAAAAk1JABAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAADKCUlEQVR4nOy9eXxcVd34/54tySSZ7HubrWlJKKW0tLRNaelGC6SIIigP1ueRRREfRVG+KogK1Z9WFB9x58FHEJQqLoAIsQtdKNDQhdKVtFmaNEuzr5Nlkrkz9/fHTaZJs03Smcw9yXm/XvPK5Myde9/nzOTeT849n3MMqqqqSCQSiUQikQiAMdACEolEIpFIJN4iAxeJRCKRSCTCIAMXiUQikUgkwiADF4lEIpFIJMIgAxeJRCKRSCTCIAMXiUQikUgkwiADF4lEIpFIJMIgAxeJRCKRSCTCIAMXiUQikUgkwiADF4lEIpFIJMIgAxeJZBpx4sQJbr/9dtLT0wkJCWHGjBmsX7+eX/7yl4O2y8jIwGAwcP311w+7n9/97ncYDAYMBgOHDx/2lO/atYt77rmHyy67jNDQUGbNmsVnP/tZampq/FqvS+Hxxx/31OXix9NPP+3Zrry8nLvvvpusrCxCQkJISkriuuuu47HHHhu0v9WrVw/ah9VqZf78+Tz11FO43e4hx29oaOArX/kKOTk5WK1WEhISWLJkCd/85jfp6Ojwe/0lEtEwyLWKJJLpwf79+1mzZg1paWl85jOfISkpicrKSt577z1KS0spKSnxbJuRkUFdXR29vb1UV1eTlJQ0aF+rV6/mwIEDOBwODh06xOLFiwFYvHgxzc3NfOITn2DOnDmcPXuWX/3qV4SGhnL06NEh+9EDjz/+OJs3b+a3v/0t4eHhg15bunQpc+bMoaSkhGuuuQar1co999xDRkYGNTU1HDlyhH//+984HA7Pe1avXk1paSlbtmwBoLGxka1bt3Lo0CG+9a1v8YMf/MCzbXNzMwsXLqS9vZ177rmHnJwcmpqaOH78OK+//jrHjx8nIyNjUtpBIhEGVSKRTAvy8vLU+Ph4taWlZchrdXV1g35PT09X161bp0ZERKhPPfXUoNcqKytVo9Go3nbbbSqgHjp0yPPaW2+9pbpcrkHbv/XWWyqgPvroo76rjA957LHHVEBtaGgYcZv//u//Vs1ms1peXj7ktYvbbtWqVeoVV1wxqKy7u1tNT09XbTabqiiKp/zHP/6xCqjvvvvukP22tbWp3d3d462ORDLlkbeKJJJpQmlpKVdccQVRUVFDXktISBhSFhISwsc//nG2bt06qPzPf/4z0dHR3HDDDUPec91112E0GoeUxcTEUFhYOKrfl770JcLDw+nq6hry2p133klSUhIulwuAw4cPc8MNNxAXF4fVaiUzM5N77rln1P1fCqWlpcycOZP09PQhrw3XdhcTEhLCNddcg91up76+ftB+TSYTy5YtG/KeiIgIQkJCLk1cIpmCyMBFIpkmpKen8/7773Py5Emv3/OpT32KgwcPUlpa6inbunUrt99+OxaLxat9dHR00NHRQVxc3Kjb3XHHHXR2dvLGG28MKu/q6uJf//oXt99+OyaTifr6ejZs2EB5eTkPP/wwv/zlL9m0aRPvvfee1/UajubmZhobGz2PlpYWz2vp6elUVlaye/fuCe+/vLwcg8EwKHBMT0/H5XLxxz/+8VLUJZLpRaC7fCQSyeSwY8cO1WQyqSaTSc3NzVW/8Y1vqNu3b1d7e3uHbJuenq5u3LhRVRRFTUpKUr///e+rqqqqH374oQqob731lvrcc88NuVU0HN///vdVQN21a9eo27ndbnXGjBnqbbfdNqj8r3/9qwqo+/btU1VVVV955RWvjust/beKLn6kp6d7tjl58qRqtVpVQF2wYIH6la98RX311VfVzs7OIftbtWqVmpOTozY0NKgNDQ3q6dOn1a9//esqoG7cuHHQtrW1tWp8fLwKqDk5Oer999+vbt26VW1tbfVJ3SSSqYgMXCSSacTBgwfVW2+9VQ0NDfVcoOPj49V//vOfg7brD1xUVVW//OUvq3PnzlVVVVUfffRRNTU1VXW73V4FLm+99ZZqNpvVT37yk175Pfjgg6rValXtdrun7LbbblNnzJihut1uVVVVdc+ePSqgPvbYY8MGXeOlP3D5xz/+oe7cudPzeOeddwZtd+bMGfXTn/60GhUV5Wm78PBw9Zlnnhm03apVq4YNhG655ZZhx9GcP39evf/++9XExETPtkFBQer3vvc9T50lEskFZOAikUxDenp61IMHD6qPPPKIGhISolosFvXUqVOe1wcGLu+9954KqEePHlUzMzPVr3/966qqqmMGLoWFhWpMTIy6YMECtb293SuvgoICFVBffPFFVVVV1W63q1arVX3wwQc927jdbs/A4IiICPWWW25Rn332WdXhcEyoLbwZnDsQRVHU48ePqz/84Q89QczOnTs9r69atUrNyMhQd+7cqW7fvl39zW9+o86YMUPNzc0dFJBdjNvtVs+cOaP+4he/UGfMmKEC6u9+97sJ1UkimcrIwEUimeb0ByCPP/64p2xg4KKqqpqVlaWuXr1aBdQPPvhg0PuGC1wqKirU1NRUNTMzUz1//vy4fDIyMtSPfvSjqqqq6tatW1VALSgoGLJdQUGB+q1vfUtdtGiRCqhXXHHFqIHBSIw3cBlIf+/PXXfd5SkbLqvo2LFjqslkUh944AGv9ltaWqoajUZ19erV43aSSKY6cnCuRDLN6Z+DZbRJ4u6880727t3L5ZdfzoIFC0bdX1NTExs2bKCnp4ft27eTnJw8Lp9PfvKTbNu2jfb2dl566SUyMjKGzbpZtmwZP/jBDzh8+DAvvvgip06d4i9/+cu4jnWpeNN2APPnz+fTn/40//u//0tFRcWY+501axbR0dG6nrhPIgkUMnCRSKYJe/bsQR1mvsn8/HwAsrOzR3zvZz/7WR577DF++tOfjnqMzs5O8vLyqK6uJj8/nzlz5ozb84477qCnp4fnn3+ebdu28clPfnLQ6y0tLUPq0R9M9fT0eMpKS0sHZUNdCm+//TZOp3NIuTdt1883vvENnE4n//M//+MpO3DgAJ2dnUO2PXjwIE1NTV7tVyKZbpgDLSCRSCaHBx54gK6uLm699VZycnLo7e1l//79nl6Nu+++e8T3pqen8/jjj495jE2bNnHw4EHuueceCgsLB83dEh4ezsc+9rEx93H11Vcze/ZsHn30UXp6erjjjjsGvf7888/zm9/8hltvvZWsrCzsdju/+93viIiIIC8vz7PdunXrAC0N+VJ54okneP/99/n4xz/O/PnzAThy5AgvvPACMTExPPjgg2PuY+7cueTl5fF///d/fOc73yE2NpY//vGPvPjii9x6660sWrSIoKAgCgsLefbZZwkJCeFb3/rWJbtLJFOOQN+rkkgkk8O///1v9Z577lFzcnLU8PBwNSgoSJ09e7b6wAMPDDtz7sWpuxcz3BiX9PT0YTNquCi9eCweffRRFVBnz5495LUjR46od955p5qWlqYGBwerCQkJ6s0336wePnx4SB28OaY3Y1zeffdd9Ytf/KI6b948NTIyUrVYLGpaWpp61113qaWlpYO2HW6MSz979+71ZESpqqoeP35c/frXv65effXVakxMjGo2m9Xk5GT1E5/4hHrkyJEx3SWS6Yhcq0gikUgkEokwyDEuEolEIpFIhEEGLhKJRCKRSIRBBi4SiUQikUiEQQYuEolEIpFIhEEGLhKJRCKRSIRBBi4SiUQikUiEQU5ANwZut5vz589js9kwGAyB1pFIJBKJRBhUVcVut5OSkoLR6Ju+Ehm4jMH58+dJTU0NtIZEIpFIJMJSWVnJzJkzfbIvGbiMgc1mA6CsrIyYmJgA23iP0+lkx44dbNiwAYvFEmidcSGqu6jeIK67qN4grruo3iCuu6jeAM3NzWRmZnqupb5ABi5j0H97yGazEREREWAb73E6nYSGhhIRESHcF11Ud1G9QVx3Ub1BXHdRvUFcd1G9Ac/ipL4caiGn/B+D9vZ2IiMjaW1tJTIyMtA6XtN/X1HEsTmiuovqDeK6i+oN4rqL6g3iuovqDdDW1kZUVBRtbW0+++dfZhVNYaxWa6AVJoyo7qJ6g7juonqDuO6ieoO47qJ6+wMZuHiJoiiBVhgXiqKQn58vnDeI6y6qN4jrLqo3iOsuqjeI6y6qN/jn2ikDF4lEIpFIJMIgAxeJRCKRSCTCIAMXiUQikUgkwiCzisZA5KwiRVEwm83CjUIX1V1UbxDXXVRvENddVG8Q111Ub5BZRZJx0t3dHWiFCSOqu6jeIK67qN4grruo3iCuu6je/kAGLl4i2mhuRVHYs2ePcN4grruo3iCuu6jeIK67qN4grruo3iCziiQSiUQiGTeKy01NWzfljZ0ANNh7kKMkxEVO+S+RSCSSKUlbl5MT1W28d7aJ863dqG6F1aHw813FpMfbWJoZw9zkSKxBpkCrDouqqrR3K7R3OQCobXMQbTMQHjy9L93Tu/ZTHLNZ3I9XVHdRvUFcd1G9QVx3vXurqkrB2Sb+faKWBruDEIuJ2PBgQowWXE4j4UFmPjzfzsmqNmZEW7l9USrZSb5bBPBScDhdnDrfTmlDB2WNnTR39uJSFHKDDfxiVzFmi5kEWzCZceFkJ9mYkxCO2TS9bp7IrKIx6M8q8uWIaIlEMr1RXG5au50YgOjQIIxGsTJF9Iyqquw+Xc9rR89jNhlIjrRiGqF9nS43Fc1dhAeb2bQ0nStnBi5ztKNHYX9JIwfKmqlpc6CqKmFBZkKDTQSbjRgMBtxuFYfTRWevi26nC4vRQHpsGMuzYlmcEUOQWX8BjD+uofoOm3WE2+0OtMK4cLvdNDY2EhcXh9Govy/zaIjqLqo3iOsumnev4ua9s028d7aJBruDaKODiKgYls+JZ2FqlBCprnpv8yMVrfzr2HlCg0wkRIQMflFVsbo76TaGgcGAxWRkVlwY55q7eOlwBZHWLNJiQyfVV1VVPqxp543jNZTWd2ALsZAeEzo4COn3NocRFmwmtq+4u9dFZUsXfzrQwdGqVm65KoWZ0ZPrPxb+uHbq71unU1wuV6AVxoXL5aKgoEA4bxDXXVRvENddJG+ny83f3q/kLwcrON/aTUSwiSvMdRTXtfOHd8t5s7BOiAGjem5zp8vN7tN1uFWGBi2AATfJPZUYuHAxNRgMpMeE0mDv4Z2ShsnUxeVW+feJWn7/dhkVzV3MTghnRrR1SM/JcN4A1iATGbFhzIwO5XhlG7/eU8Kh8ubJrMKY+ON7IgMXiUQimQSOV7VRUNJEUmQI6bFh2EK0Du/MuDDCgkzsOFVHVYucq+NSKKqzc66pi+TIoUHLaBgMBuLDgzlW1UaDvcdPdoNxu1X+dew8r5+owRpkIit+4mNVrBYTlyWG0+N08+cDFRSUNvnYVl/IwEUikUgmgcPlzaio2EIsOJwuKlu6KW3XBmPG24Jpdzg5XtUaaE2hOXKuBbdbJcQy/iyh6LAgWrp6OVHd6nuxYdhzpp6dH9YSFx5EXHjwJe/PYDCQGhOK0WjgH0eqOFnd5gNLfSLHuHiJCPeeB2IwGLDZbMJ5g7juonqDuO4ieLd0ahfDbadqabT38HZxI+2O/km5zMA5QoNMhAaZaOl00trt5LJEG5cl2IgMtQRS3YOqqlQ2d3OsqpXalg6ijME8X1BORlwE81MjSbCNr4fDX5Q3dWILGdpmDqeLlq5e2jp7aXRZIKqXyLBgzAPG6BgNBixGI9UtDr97nmvqZMepWsJDLESHBnnxDgO9hiBg7O/5jCgrZxs7eO1YNakxoURaA/sd8sffpswqGgOZVSSRSLylubOXE9VtnKxu40RVGyeq26huHf72T0SIGRWwO0aeWTTBFsxliTbmJIYzJ8HGZYnhzEm0TerFqKTezpuF9RTV2unsVQgxmzAaDShuNz1ON1GhFubPjGL93EQShxlXMlm0d/fyyMsnaOtWcLlVWrt6aely0trVi0MZOkDUAERYLcSGBREdFkRMWBA9ThfXpEfzwPWX+c2zR3HxzL6zfHi+nTkJ4X65sCtuN8V1HVw/N5FPLJoZ0MDeH9dQGbiMQX+jt7S0EBUVFWgdr3G73VRWVpKamqrLkf+jIaq7qN4grnsgvZs6ei4EKdVtnKxuHzFISY8NJS48iPZuhSuSI0iMDCHEbMTmaqVJjaDW7qCkvoNZceG0djsprrNzvm3k//wTI7SAZnZCuNY70xfQRAzT23ApfFDRwkuHKmnrdpIUEYItxIwBsLlasZuicAOtXU7q2h2kx4by6WXppMeG+dRhIL2Km8qWLsoaOilv6uRsYydlDZ2UNXZS2z56T0l4sJmoUAuq4qSh203vMMFMP0kRIcxJDCcrPpzZCRcesWFBlxwEHKlo4fdvl5EabSXY21taquppc7w8fktnL129Cg+uv2zSM41au7QAvrbNQUNTE1+8caFMhw4EehxBPxoul4ujR4+SkpIi1IUIxHVv6XBw9OhRouMSiAizBlpnXIja5pPl3WDv8QQo/cFKzQiBRWZcGPNmRHLljAjmzYjkipRIIq0WGuw9/HZvCTVtDgwGLVMkvreWemMonT0u1s9N4r7rZnnGZ9gdTkrqOyiu66Cozk5RfQfFdXZq2hzUtfdQ167ddhpI/wV3YO/MnMTwCQU0RXV2XjpUicPpGtQzYFBdxPfW0mGNwGgwERMWRKTVwtmGDl48cI7Prpx1SbeO3G6VmnZHX0DSQVljV9/PTipbunG5R/5f22oxEWIxkhQZQlRoENFWC1GhQUSFWrCYjBhUF5ndRZwNmUOnU+shG/io7+ihV3FT2+6gtt0xpH2jQi3M6QtiBgY1KZFWr+biUVWVg2Va1o/XQQsXvisd1ghUvHtfVKiFunYHRytaJyVwUVWVs42dfFDRwvvnWmjudGI0AA67z48lAxeJ5BJxuVW2n6xlf0kd15jg52+WsP7KFJbNih37zRLdUW939N3qafcEKcP9N28w9AUpKZFcOSNSC1JmRIwYJMTbgvmv3Az+eriSc01d2kXUBo0dvSxIjeKOa1IHDSq1hVhYmBbNwrToQftp9wQ0dor6gpriug7PxXa4C25yZMiQ3pk5CeHDjgeB/jTdGtq7FWYnhI3Zy2AyGpgVH05RnZ23ixq4bVHqqNurqkpzZy9ljX29Jo2dlPf9LGvspGeU3pDQIBOZcWFkxoUxKy6MjL7nmXFhFNV18Ny7ZcyKCxs1Q8dgMBAWbCIs2ExqjHZRtzuctHY5ufvaDHpdKqX1HRTX2ymp76CkoYOqlm5au5wcKm/hUHnLoP1ZLSayEsKYk2AbFNSkx4ZiGeBR1dJNUZ2dBNulD8YdC4PBQGSohcPnWlh3eaJflzVwu1V2na5j28laOnpcxIYFMSchHJPRQE+H7+dxES5w+fWvf81PfvITamtrueqqq/jlL3/JkiVLRtz+b3/7G9/5zncoLy9nzpw5PPHEE+Tl5U2isWSqc7i8mfyTNUQGG3Gr0Nbj5B/vV5EUEUJGnP+6zac7zZ29fFil/fd6pKKFeTNjCBvnGi517Q7PWJRT57Wfde1D02ENBpgVF+YJUK6cEcnclIgRL/wjkREXxleun8OZWjs1LR04zp7nvutmMSc5asTZXS8mIsTC1WnRXD1MQFNcdyGgKa6/ENDUtGmPiwOalMgQZifauKwvqJnTF9TUtHZztrGTlKgQr2+NmIwGYsODOFLRyrrLE4kKDaKjR6G8ceAtnQ7Kmrooa+gYMEB5KBaTgbSYUDLjwpkVrwUlGbFhzIoPI8EWPKLTFSkRJEaEUG/vISVqfL2ede0O5vV9vgaDgUXpg9u3u9fF2cYOLZAZ8Chv6qTb6eJkdTsnq9uH1CM9NszTS6MCta0OElP9H7gAxIQGcb6tm5q2bmbFh/vlGG63yuvHa9h+qpZIq2VSeneEClxeeuklvva1r/H000+zdOlSnnrqKW644QbOnDlDQkLCkO3379/PnXfeyZYtW7j55pvZunUrH/vYxzhy5Ajz5s0b17H1nLUwHAaDgfj4eOG8QSz3doeTv79fxYnqNtq7nWztMhNvayI0yMw/jlRx/6qscV9MA4FIba6qKm+daWD7h7W0d/VwtTWYnQXnSIhs4ONXz2TejKHTtquqSl17z6BbPSeqh5+zw2iArPhwz0WsP0jx1cJ2wWYT82dGMTcpnIP2eGYn2rwOWkYjIsTCovToIRfctm4nJfWDe2eK6+3Utfdwvs3B+TYH+4oGT7wWZbVg7gseYsKCiA0LJiYsqG9iNANdxjD6M1wUt5v2boWWLu12S0VTF4fPtdDS2Uv9KHOiGAyQEmn1BCYXelHCSYkKmdCcJmHBZpZnxfLyB9V09CjDfGaD3ftpsPdgNhlZnhU34t+ANcjEFSnarb+B9C8bcHFAU9rQQVevy/P7QPafbSIixExM36Dg6LAgYkK158Oncg/vPRZBZiO9ivbd91fg8k5JIzs+rPUMch7KNM8qWrp0Kddccw2/+tWvAG1gXmpqKg888AAPP/zwkO3vuOMOOjs7ef311z1ly5YtY8GCBTz99NNeHbN/cO758+dlVpEEp8vN8ep2Cs62UFDWwonqdlyj/AWZjQbmpdhYmhHN0swoFsyMINisz5VoReFoZQsvFlQQZDGSYAvGaDDgcrupaukmLNjMZ1dkYjab+LDGzqmaDgpr7ZyqsdPU6RyyL6MBZsWFMjfZxhXJNuYm28hJDCdUp6sF+5K2bieljV2UNHRS2tDZ97OLho7eEd8THmQiOtRMeLCJjh4Xrd0KHT0uRruIxIZpU9hnxFo9PzNiQkmNCfHL34LT5ebvhyvZf7aJ5IiQUXvFVFQa7T109LjIm5fEurmJPgve3apKbXsPZxu7ONuote27pU00djpxjnLSsFqMRFvNRIdaiLaaiep7HmoxTsituL6DG+clkndlyqVUZ1jaup38/M0iHE73iJP+Obo62HznyumZVdTb20toaCh///vf+djHPuYp/8xnPkNrayv//Oc/h7wnLS2Nr33tazz44IOesscee4xXX32VY8eODXucnp4eenou/JfQ3t5Oauro92slUxtz7EysGQsJSV9ASNqVGIMHd4U6m8/jKP+A7vKjOBvKCUq+jJD0+YSkX4UlKmnQtqrSi6OqEEfFMRznjtNbWwxusQZ+6w2TLZ6gpNkEJ2URlDSboMTZmMKihmynul04GyvorSuht7ZU+1lfhuqcnJlSRcEYEo4lNg1L3OCHOTxmxPe4e7pwNlehtJzH2XweZ3M1Sks1zubzqL1dk2gvBkZrBJbYVO0Rl+p5bo6IH/E97p4uXF1tuLvtuB3tuLrt2vPuvucO7bm7246r76fq9P+cNN4yLbOKGhsbcblcJCYmDipPTEzk9OnTw76ntrZ22O1ra2tHPM6WLVvYvHnzpQtLhMUYGoU1YwEhGVcRkrEQsy1u0OuurjYc547hKD9Kd/lRXO31g15XWmvoKnwLAHNkIsFp87VAJm0+Zlss1oyrsGZcBWgno56qDy8EMvVloIq1oOfkYcAcnUxQYlbfYxZBiVmYQoe5NdQfpNSW0FNbQm9dCc76clRFBilj4XZ00FP9IT3VHw4qN4bYPEGMyRaLq63OE6S4u1oDIyso7u52eqpO0VN1alC5IciKJWbmkKDGHJWEMThU+6cpOtnr46hKb1+A0xfQDApuLjwfFAg5OnR/DhImcJksHnnkEb72ta95fu/vcSktLSUmRvuPw2g0YjKZcLlcg1a+7C9XFGXQYmkmkwmj0ThiudM5uAvbbNY+FkVRvCq3WCy43e5BKduKorBr1y7Wr18/KE3UYDBgNptHdNdDnZxOJ7t37x7R/eK6Xmqdup0ujlS2c/BcOwVlLRTVdw5yDDIZuDotkqXpkSzLiCI7MQyjIW+Ie3NHN4fe3cd1q9dhCwsZtq6lDZ28V9bMoXNtHK5oo5VQrFmLsWYtBrRJyRanRbAkPYrcrFgyooMHta+/Pqf+Nt+wYQMWi+WSvnu++JycLjfnWno4Xd/Jh+fbKazt5Ex9B129Q0+oRlRiQi3EhQcRZDSQEW3hW3k5hFiuG9V9sus0sFxRFHp7e9m9ezdr164lJCRk0s8Ro9XpteO17DtTx+yEgYPLDagYMapO0h1nOReSiWowoWIAjBhw43a7KWvs5LarU1k+J143dWrs6KG6rZeuLgftZ4+QmLOYWYkRRIUGT+p57+m3Sqhp7SG5bwDrxYsmaqnO6kXl2q3QiLazlJpm4FDAobhxOFUciopDceFwuulR3NrvTjcOxY1bBYM5CLMtFmzeZzgaAFuIdosqKtRCZIiZSKuZKKuFSKuZmLBgoqwWOh09vPlhHUkRFiKtQZhMpmHr5Ojq4PE7V3t9fG8QJnCJi4vDZDJRV1c3qLyuro6kpKRh35OUlDSu7QGCg4MJDh464jsyMlKoCeicTichISHYbDYsFn1MG+4t/nZ3uVVOnW/j7eJG3ilu5P1zLfS6Bv+xzU2OYOWcOFbMieOajBiv1j4JCwvjREgIcTGRI3pfFR7OVZmJfB5tNP7pWjv7SxspKG3iQFkz7Q6F3UXN7C5qhp1niQsPZnlWLMuzYsnNiiUtMtQvA2j72zw8PHzSvy8Op4vCmnZOnW/n1Pk2Tp1v53StfdgJwkIsRqJDg7CYDMxJsJEQbmGR6RxVYVm4MXKm1s76+Skkxes/Fb2/zaOionT3N5qbbeRwdRdOY/CQweUG1UUIIQRZbaiGwX8X9XYH8bHBLMtJxaaT5QoAoqJg9kytzfPPf8i1c9MC0uazZiRSYa8n2Dq+bEOD6iLVEIxijRnS5sOhqipOl4rD6eJMXTsr5sQzMzpUm02400lLV2/fw9k3w3AvrZ1O7D0KKtDuUGh3KFSMY/kDs9FASN88OiEWU9+cOibMfujlFCZwCQoKYtGiRezatcszxsXtdrNr1y6+9KUvDfue3Nxcdu3aNWiMy86dO8nNzR338UWalAs037S0NOG8wT/uFU1dvFPSyDslDewvbaK1a/B/RimRIayYE8eKOfFcmxVL7AQWPRuvt9FoYG5KBHNTIvjsylkoLjcnqtvYX9pEQWkTh88109jRw2vHzvPasfOAtg5J7oBAJjnSNxPdTdb3pd3h5MPzfUFKtRaklDR0DDupmC3YzNyUiL7sngiuSIlkVlwYhTV2nnu3DIDYsCC6XZH0KG4qWrpJjAxhcWb0kH3pET3/jc6KC2dWXBhnajuGmcfFQLspkouzRVxulaaOXm64IlE3ayxdTKDbPDkyBPeEhpUO3+Yjbm0wEGQ2YDBATFgw63ISyU6yjfk+p8tNqyeY0QKcgc9bOi8EO+fbHDS096C4td4dxa3S0aPQcVGc4u7x/RgnYQbngpYO/ZnPfIb//d//ZcmSJTz11FP89a9/5fTp0yQmJvJf//VfzJgxgy1btgBaOvSqVav40Y9+xMaNG/nLX/7CD3/4w3GlQ8u1isSktauXgtIm3i7RelUqmgf/8diCzSzLitV6VWbHkRk39iRbk02P4uJoRasnkPmgsmVINsKsuLC+QCaOZbNiJhRw+YvGjh5OnW/nZHUbH55v5+T5Ns41DX8SiwsP6ks17Z9tNoLU6NBhZyNVVZUDZc38+0QNDR09qKo2h8jMaCsfv3omlyWOfYKWjE1RnZ1n3ynD4XSRFjN6T5/LrVLa0EFqjPWSZ86dypTUd/CLXUUkRoQQGuT/foMGew8qKg/fdLnP17c6WtnK03tLmZMQhtOt3aLqdrpweB7a7/b2drZ948bpOTgXtPTmhoYGvvvd71JbW8uCBQvYtm2bZwBuRUXFoEh6+fLlbN26lW9/+9t861vfYs6cObz66qvjnsMFxJzy//jx48yfP99z71EUJuLeo7g4cq6Vd0oaeKe4kRPVbQz8J95sNLAwLYoVs+NZMSeOq2ZGTmieCF97j0aw2cTSWbEsnRXLV9dDV6/C4fKWvkBGq+PZvsm9XjxQAUBOks0TyCzJjPH6ZHUp7qqqcr7NwanqNk4O6EkZae2YGVFWrkjRelDm9U2LP9qkYhdjMBhYNiuWeTMiOX2+lcaKYpIzs8lJiRQq1Vzvf6OXJdr4jyVpvHSwgqK6DpIjtbWKjKjE9tbSFJSEC4Nnvpb02FA+vTRD10FLoNs8IzaU9NgwKpq6yIjz/vJrUN2eNlcN3p+3mrt6WJOd6JdFOcOCTFhMBpwulWCLiWCzadjj9HRY2ObjYwsVuAB86UtfGvHW0N69e4eUfeITn+ATn/jEJR934MAtEXC73VRUVDBv3jxdnhRHwxt3VVU5U2fnneJG3i5u5GBZM93OwcHl7IRwVsyOY+WcOJbOivXZBGKX4n0phAaZue6yeK67TEuZbHc4OXi2mf2lTewvbeR0rd3zeO7dcowGuHJGJLlZcSzPimVxRvSQ//JUVaWiuYvSujbsFRUkps8hJWbkiarcbpXypk4tQDnfxqlq7WdL19A5UvqnxL8iJZJ5fYHKFSkRI0xSNX7Cg81cNTOS/OP1zE1ejEWgoAXE+BtdkBpFeLCZXYV1nKmzU93aTZjFQGZoG+83htPt0iarW5Udz/rLE0kI4OrQ3hDoNjebjCybFUtxnR3F5R7HP08qEa42mkgce9M+OnsUgs0mFqVHTch1LNJjw0iJtlLf3uNZNmF4fH9TR7jARTK16e51UdGozTKpuNwMHD9X2+bQxqkUN/BOSRONF91MjQsPZsXsWFbMiWfF7DiSRpgQaaoQEWLh+rmJXD9XO5k1dfTw3tlmz2Dfs42dHKtq41hVG0+/VYrFZGBhajS5feNjFqRGsruwgV2n63D09LIhAn6zt4RbF6WxKD0Gp8tNcV2HZ8DsqfPaLZ/O3qG9j2ajgTmJNu1WT0oEV8yI5PJk3802Kwkc2to7YVS1dHOsspXa1k5ohfkzI0mPj2D+zCjiJ2HtnanC/JmRpMWGUtnSRWacf2azVVWVypYuFqVH++0YQWYjyzJj+cuhCtyqinESb7XLs4pENzR29PDHgnOca2hnTRg8v7+c9IQIDpxt5t2SRoovmjY7xGJkaWasJ/snO9Gmu3Eqk0lseDAb5yezcb42z0Ntm4OCs43sL2lif2kT1a3dHCxv5mB5Mz/fVUyw2Uik1UJyZAjZCaGU2+FUq50D5ScIMhspru8YMbMnJynCM2B2XkokcxLDvcq8koiJwWAgNSaU1JhQLTMn/0P+MzdDd9lQImALsXDz/BR+/04ZrV29RIX6pgdyIOfbHMSFB/ORq1J8spzESMyfGcn2U0E0dvRM6i1CGbh4iR5H/o+G0WgkOztbKO/84zUUlDbidqs8WRZMlb1kUCejwQDzZ0Rq2T+z47k6PUpXYxr01uZJkSHcunAmty6cqf0H1tzN/tLGvltLWo9VvV17HKtqQzsdDF4kbqTMHl+PD5ooemvz8SCqu6jeoB/3K2dEsmJ2HG8W1hFkNo45UFfFQIs5rm/OnNFp6erF4XTx0QUpPss6HInY8GBWzonj9eM1WC2mYZdX8MZ5vAiVVRQIZFaR/+gfp/JuSRP7SxrZV9wwJGsmNiyIG+YlsXJ2HLlZsX7572Q6oqoqLxSc4y8HK+h1ualu7caAgXhbEBajkdsWzWTj/OQRM3skEsml4XC62HrgHAfKmkmNDvXJYqzNnb00dfRww7wkPjI/ZVL+dhWXm5cOV/J2UQNJkdYhA3QdnR1869ZF0zerKJBcPGuj3lEUhYMHD7JkyRLP7I16oKqli/0lTbxT0uj5r38gFpOB1Ggr8yIc2M1R3LViNqsuG3n9Dj2h1zYfDoPBwKrL4jlR1YrRaODmeYkk9lZzwB5BdLiV/8xNH3VxOr0gUptfjKjuonqDvtxDLCb+Y0kaRqOBA2ebsYWYSYoIGfZ2t0F1k9hTRV3wzGGzilxulcrmLlRU8q5M5qYrkyftHw6zycjti2YSbDbyVlEDDfYeEmzB2ELMGAwGDH5YPkCsb10AEa1jSlVVGhoaAu7d0tlLwdm+QKWkkfKL5vGwWkxckxnDitmxzEuJ5FB5M+ca7KwKbactLoGlmSMv7KY39NLm3pIeG8rG+clsO1lLaUMHs2ydRIclcPuimUIELSBemw9EVHdRvUF/7qFBZj61JJ302DB2nKylqK6DxIhgIq0WzO4ewp2NhPY2YXE7MAdFMLPtML2mMDqDYumyxKFgoqmzl8aOHtJiQsmbn8yCmVGT3ksabDZx68KZZMWHc7CsmTN1ds63dWO1mMDR7fPjycBF4lO6e10cLG9mf0kj75Y2cup8OwPPESajgatmavd3l8+OY2Ha4HEqV6dHU93UwckDVXxycaoc8OlHDAYDa3ISmZsSSUltG42F53lgzWxiI0ZLbZRIJL4kyGxkTXYCs+PD2XOiDHvZ+ySWHydZrSPc4CAEJ25TEEWpm7ii9jUM7h661RDshFBlSiUo+ioWXb6ItXNn+myqgYlgMhpYmBbNgtQoqpq7OFl6jtb6Stp7G3x+LBm4SC4JxeXmWFUb+0saeaekkQ8qWoes+5OdaGP57FhWzNYmRRvtv/kQi4m02FBOgl9Hw0sukBgRQozVRH4hRPhhoiqJRDIGjnZSa/bwn53v4jBX0RKmUtsbTIs7li6XBZdb+weuRE3BbFAIM/YSbe4hJ6iISFMFwa0noeY6yFgJ5gCOA3S0Y6g5Suq5/aS2VUNvB02uXu738WFk4OIlep0gaiRMJhMLFizwubeqqhTXd/BOcSP7Sxs5cLYZe8/g8T8pkSFcO1tLUc7Nih13mpy/3P2NqN4grruo3iCuu6jeoEN3VYXa43DyFWgqxmCNxpqUg9VkIRmVHqebzl4Fh6LSqJYTnx6F1WwgLNhMUH9mn+IAey28/weoOQbzPg7RGZNfj+r34dQr0HoOTMEQGgthcZhCfD/GRWYVjYHMKoLq1m7e7Ruj8m5pEw32wQNqo0It5M6K5drZcVw7O46MWP+sYCyRSCRTBpdTC1hKdoLbpQUbpkvo8XR2Q/NZCI2GebdB5iptDgl/43LCyZeheId2vKh0MF7oE2nvdBD5ke/JrKJAIGJW0b59+7juuuvGPXq+f4HCd0sbebekibLGzkGvh1iMXJMRowUqWXHMTYnw6W2dS3EPJKJ6g7juonqDuO6ieoOO3JVeOPZnKHkTwhO13onRNlcN7OvM5LqwMsyGEfoaLFZImAvt1XDkj1ogc9mN/g1e3G448Xc4kw/hSRA6NJlCUX1/fLG+dQFEtI4pVVWx2+1eeXf3ujh8rrkv86eJk+fbBg2oNRrgqtQors3SelT8PfHbeNz1hKjeIK67qN4grruo3qATd7cLTvxN62mJSIWQsXshVAzY3SF9k7mN4m4wQORM7dbRib+DORiy1vrO/WIqD2g9LbZksEYPu4k/JqCTgcs0RHG5OV6tDah9t6SJ98+1DBlQOych3HPrZ+msGCIESY+VSCQSXVPxnha02GZ4FbRMCFsStFVrt3Ci0iE2y/fH6GqGD18Fo2XEoMVfyMBlCuJwuthfpKWgHS5vZsmseM42dvJuSSPvlDRx4GzTkAG1yZEhLM+KY8WcWJZnxZGo81VeJRKJRDg66uHDf2qDV61R/j1WRAo0noaT/4DlXwaLj8/pVYehrQriL/ftfr1ABi5eoptR6F7w6gfV7Pqwho4OG5WnT9LhcNHa7Ry0TUSImeVZcVw7O5bls+OYFRemmwG1JpOJ3NxcodocxPUGcd1F9QZx3UX1hgC7q6oWtLRXa2NRxoEJN7mh5zAxjgwdgwGiM7WspbN7IPumcQqPgssJ5e9AUDgYR2/LcTl7iQxcvCTQi3J5S4/iYseHtbx3toWuXpenPNisDajtn0/lipRI3c6TYjQaSUhICLTGuBHVG8R1F9UbxHUX1RsC7N5aAdVHIGImDDNt/2gYDZBg7hx7w4sxh0BwBJzdC5nXQVDY+PcxHPZa6KiD0LgxN/XHZUaMq7EOcDqdY28UYNq6nXz7lZPsPt1AV6+L6CCVrFgr91ybwbHHNvCnzy7lv1fPZv7MKN0GLaC19RtvvCFEmw9EVG8Q111UbxDXXVRvCLB79fvQ0w4hkeN+q1M18kZ7Nk51Apfs8CSw10DN8fG/dyQ66rSspaCxZ9l2uuXgXMkIvPlhHY++eoK6dm2OlSuSw/lMaivV4Ulsyp0l3NT5oqWf9yOqN4jrLqo3iOsuqjcEyL23EyoKwBoz4fRkhQmew00WMJigYj+kLfNNenRvB6hucDqg1w49HVpZ/6Pnwk+z3X7px7sIGbgITnNnL5v/dYp/Hj0PQGZcGE/cNp/LE0LZ/eZ27luZRZg1OMCWEolEMo1pq4auJohMC8zxQ2Oh5Zx3PT6qCt0t2u0ge83gnx212s+WcuhsZNTU7D4MXmwzXmTgIiiqqpJ/opbv/vMkTZ29GA3wuetm8dXrLyPEYvJ0hQaZ5d1AiUQiCSj2Gm1AqylA6wgFhWuBS2MxBNuGBiSDftaBq2fsffZjCYXgcO0Y/Y9gW9/PcJzOYOBJn1ZHTvk/Bv1T/re2thIZOf57k/6g3u7gu6+eYtupWgAuSwznJ7dfxVWpUZ5t+idastlsuskW8hZR3UX1BnHdRfUGcd1F9YYAun+wFYq3TTh1WFXB7g7GZuwZ/k6P0jP4Fs2g5323cnrsoLqGefMIWGO0ieVsSQN+9j0wwLG/aJPdjdGD09bhIOoWOeX/tEVVVV4+Us33Xv+Qtm4nZqOB/14zmy+uyRp2Jlur1RoAS98gqruo3iCuu6jeIK67qN4QIPeuRjBeQm+L0kNoyxnoaRsmMOkAV6/3+wqJGhCEXByYJGtLEIQnjj7vi9KrTaTX1TihwcaXigxcvCTQg9HOt3bzrVdOsPeMNrHcFSkR/OT2q5ibMnwEqygK+fn55OXlYbGINeutqO6ieoO47qJ6g7juonpDAN1dveNOgQa0rpbGM1DyJubejtG3NQUPc8tmwE97LVx1B8y/Y2J1GIg5CDJWwAd/1AbpjlI3xQ/JyzJw0TmqqvLng5X8ML+Qjh6FIJORr1w/h/uum4XFJMevSCQSie4ZY5K2YXG0QvFOaC7FAHQGxWGNTMAYfFFQ0v98rPEzPXZtXhdfMfMaKN2tzU8TneG7/XqBDFx0TEVTFw+/fJz9pU0ALEyL4ie3z2d2gi3AZhKJRCLxGksYuL2cO8btgurD2sy0bicYjLhSl7M7+i5ujDyL0XAJM9GafJhhGhYLc2+BQ7/XgqyQKN/tewxk4KJD3G6V5wvK+fG2M3Q7XYRYjHz9hhzuWp6h64njJBKJRDIMUalQ/vbY27VXQ9E26NSGBBCZCpfdiNsaj9t+CWNk3C5t/pZwH88anJYLzeXawGMV/6+/1IfMKhqDyc4qKm3o4Jt/P87hcy0ALJsVw48+Pp+MuPFN1ayqKoqiYDabhRz5L6K7qN4grruo3iCuu6jeEED38x/AOz+D2MuGv22kOKDsLW07ALMVstZA4pVgMKCq2lgRM+6JzR/X0w7drbDuuxCRfCk1GYrSCyf+BqW7wGCGqLRBdZRZRVMYxeXmd2+X8bM3i+hV3IQFmXgk73I+tSQN4wR7Wbq7u7HZxLytJKq7qN4grruo3iCuu6jeECB3W7I2FqXHPrhXQlWh4TSUvqnNrgtasJK1RpsfZQDdbgs24zjmVxmIow2skRAWP7H3j4Y5CK66E2KztEUkG09rgVdojFZnPyBHd3qJP7OKTte2c+tv9vPEttP0Km6uuyyeHV9bxaeXpU84aFEUhT179gQ8G2oiiOouqjeI6y6qN4jrLqo3BNA9PBESLtfW+Omnu1XrqSj8pxa0WGNg/p2Qs3FI0KJgZE9n1sQydFRVC1zScsHkp74Ko1FbTmDVN2DxPVqvS08HNBWjNJb4/HCyxyWA9CpufrO3hF/vKcHpUokIMfPdj1zBbVfPEK4LViKRSCQjYDBogUPVYejtgtrjcO4dcCvaOkJpudqF3+iHS7KjVZtrZcYi3+/7YqzRkLUWMldrSxx01EJDPbDVp4eRgUuAOFHVxtf/fozTtdoCVOvnJvKDj80jIcKH6WoSiUQi0QeJ87QFD4/8QRtzAlrPxJwbtLWE/IGqgv08pF8LETP8c4zhMBohPF57WJp8vnsZuEwyDqeLn+8q5pl9Z3G5VWLCgth8yxXcPD/Z570sZrO4H6+o7qJ6g7juonqDuO6iekOA3Ltb4M3N2q0h0OZTyVqnBTNenvfNjGO6/n7s57VbUNl5vlkVWifIrKIx6M8q8sWI6PfPNfP1vx/nbIM2COsjV6Xw+EfmEhsuV2+WSCSSKYeqwsl/wLZHoLNeK0tdqt26SbpqYhPTeYuzG1rLYeF/wpz1/jvOGPjyGtqPHJzrJW73xCf96epV2PyvU9z+dAFnGzqJtwXzv/+5iF/eudBvQYvb7aa+vv6SvAOFqO6ieoO47qJ6g7juonrDJLs3n4U/fRz+ca8WtMRdBne9AXf+BRLmalP5q955uFWoV8Jwe9vNoPRAcymkLILMVROvgw/wR1vLwMVLXK4JdNMB+0saufGpt3nu3XJUFW5fNJM3v7qKG65I8rHhYFwuFwUFBRP2DiSiuovqDeK6i+oN4rqL6g2T5K70wr4n4Te52pT4pmBY8224/x1tfZ/QGC3zJnKmlgrtHtvFhZGCrnRc3lyyFQc0FUPyVbDoM1q6cgDxR1uLe6NS59gdTrb8+zRbD1QAkBIZwpbb5rPqMj/k0UskEokk8JwrgNcf1AIS0Ho7bv6ZNsfJQKLTYenntenyGwohKh2CfTC3TGeDlnI9YxEsvnvSZrKdbGTg4gf2nKnnWy+foKbNAcCnl6XxzRtzsIWItZKqRCKRSLygqxnefByOPK/9HhoHN26BKz8x8qDY6AxY/mU49QpU7IeuYK0XZiIp0YoDWs6BJQSu+Jg2GDdofLOti4QMXLzEm4yf1q5evv96If84UgVAWkwoT9w2n9wsP6W6jYLBYMBmswk5H4yo7qJ6g7juonqDuO6ieoMf3FUVTvwdtj9yYX2hq/8Lrt+s3RIai/B4uOazkDQPPnwNGovAaOmbaTfME/QYULEZHRgYMMilf2K5jjowALGzYd7HtYnudPTZ+ON7IrOKxsDbEdHbTtby7VdP0tjRg8EA91ybyUMbLiM0SMaGEolEMuVoKoU3vgZn92q/x+dot4XSl09sfz12qDkG5e9CU4nWiwLaLLomC2DUBvMqDnD1Tf0fbNMG+qbnaqnVZv1lqPojq0heVb1kpJHRjR09PPbaKd44XgNAVnwYP779KhalR0+m3hDcbjeVlZWkpqZiNIo1BltUd1G9QVx3Ub1BXHdRvcFH7kovvPtz2PcTLYAwh8B1X9du+1zKQNhgmzZ4Ny0XWsrBXgPt56H5LG5HJ5VKNKmWVoyhkRCTpfXKRM7QJpbTUQ/Lxfgjq0gGLl5y8choVVV57dh5Hn/tFC1dTkxGA/evmsUDa+cQYvFjbr6XuFwujh49SkpKinAnF1HdRfUGcd1F9QZx3UX1Bh+4n9sP/3pQS2UGmLUGNv506ODbS8Fo0vY3YJ8up5Oj+fmk3JCH0SLWWEmZVaQT6todPPrKSd4s1BbMykmy8eQnrmLejMgAm0kkEonE53Q1w87vwgd/1H4Pi4cbfwTzbtN1b8dURZhwubm5mU2bNhEREUFUVBT33nsvHR0do77nmWeeYfXq1URERGAwGGhtbb0kB1VV+euhSq7/n7d4s7AOi8nA19ZfxmtfWiGDFolEItEjXc1QsgsO/g4KfqWVffCilrrc2zn6e1UVjv0FfrX4QtCy6C740iG48nYZtAQIYXpcNm3aRE1NDTt37sTpdHL33Xdz3333sXXryKtOdnV1ceONN3LjjTfyyCOPXNLxa9ocPPjqQd4ubgTgqpmR/Pj2q8hO8kHuvR8wGAzEx8cLO/JfRHdRvUFcd1G9QVx3YbxbK6Dsbag6CJ2NYLJgMFqJN4ZjKC+A8t3aOJH05ZC+AsIuyv5sLIE3vgpl+7Tf4y+HjzylreI8yQjT5sMwbbOKCgsLmTt3LocOHWLx4sUAbNu2jby8PKqqqkhJSRn1/Xv37mXNmjW0tLQQFRU1rmP3j4ie8/W/02sMIdhs5GvrL+PeFZmYTcJ0WEkkEsn04fwHcOSPWqpwWLw2r8rF6wK5nNrrjlaInQOL79LmVlF64J2n4O2f9g2+tcKqb0DulwI+C62ITNusooKCAqKiojxBC8D111+P0WjkwIED3HrrrT47Vk9PDz09PZ7f29u15ccdTjfXzIliy61XkJVgw2Qy4nK5Bo2YNhqNmEwmFEVhYDxoMpkwGo0jljudzkEO/auXKoriVbnFYsHtdg8aBOV2uykrKyMra/CgMYPBgNlsHtFdD3VyuVyUl5eP6H5xXfVSJ5fLRWlpKdnZ2Z79D2S4z0kvdRrLfTzfvcmsk6IolJaWkpWVRVBQkN/+nvxRp+HcJ/McMdE69fb2UlxcTFZWlsdPL+c9g8GAueEU7kPP4lKcEH8lGAwYUDGj0us2UtwTR1ZwEyajEWNEKiZbEq7GEtzv/R+GGQsxvfVDDE0lALhnrcV144+1gEYFk9sdkDoZDAaKiorIzMzEZDJ59Tnp4VwO03hwbm1tLQkJCYPKzGYzMTEx1NbW+vRYW7ZsYfPmzUPKb0lzsS6lkcKDb9GZlsbChQs5fvw4FRUVnm2ys7PJycnh4MGDNDQ0eMoXLFhAeno6+/btw263e8pzc3NJSEhgx44dgz7sNWvWYLVayc/PH+SQl5dHd3c3e/bs8ZSZzWY2btxIY2MjBQUFnvLw8HA6OjoICgrixIkTnvL4+HiWL19OcXExZ86c8ZSn6axOiqIQERHBoUOHPOU2m421a9dSWVnJ0aNHdVunzMxMFEXx6nPSW52Sk5Ox2WyX9N0LRJ1KSkr8+vfkzzqVlJQE5Bwx0TqdOHGCqqoqSkpKxv05+b1OYVbW9uygUonjqHkB9A2DjDd1sDysguLeOEqc2gMgzdLCQmsNp0IWE1W8nbQDvwRACYnBfPOTvNeWREPBh8CHgauTzcbKlSspKiqiqKjI689JL+fyZct8f2stoLeKHn74YZ544olRtyksLOTll1/m+eefH/ThACQkJLB582a+8IUvjLqP8dwqGq7HJTU1lT/vPc5ty3MA/UW0w0XpiqKwY8cObrzxxkFpfyJE6U6nk507d47oHujeiZHc+71vuukmLBaL7nonRqvTWO6B7p0YqU69vb3s3LmT9evXExISorveidHqNJy7CD0uDoeD7du3s379eiwWi67Oe4aibZhP/AV3/DxchgHnDlTMBhWH28T2jmzWhxdhMbgxqm5M9SdQS3djULpRAXf2zXDLLzGFxeijTgYDqqqSn5/vafP+cj2c98Yqb29vJy4uburcKnrooYe46667Rt1m1qxZJCUlUV9fP6hcURSam5tJSvLtKsvBwcEEBw+dfXDd3GTPF6Yfk8nk6bYbSP8H6G35xfudSLnRaBx2XgKj0Tjs9iO5661O46mrXurU37U73s9JD3UazX247Udzn4w69Z9o+y+gIzmOt3wy6jSce6DOEeOtU/8xBh4n4Oc9ZzdU7ofgSIxGMDJ04jOToa/NDW4s3Q1QtB3aKjAAhMVjSLgcU/oyCI3WR5366A8eLm5z0M95b6xyXxLQwCU+Pp74+LFXS87NzaW1tZX333+fRYsWAbB7927cbjdLly71tyYAZnPgJ5UbD0ajkbS0NOEmiAJx3UX1BnHdRfUGcd116117UptpNmbWiJsYUUk31WMq3weVBaC6tEUN01fAzGu0affrPoS2SohKm0T50dFtm3uBP5yFyCoCuOmmm6irq+Ppp5/2pEMvXrzYkw5dXV3NunXreOGFF1iyZAmgjY2pra3l8OHDfO5zn2Pfvn3YbDbS0tKIifFiASz8MyJaIpFIJD6m8HU4/pK2ds9ItJ7Telm6m7XfY7Jg9nqwRmm/qyo0FMK1D8LMRf42nhb44xoqTPj24osvkpOTw7p168jLy2PFihU888wzntedTidnzpyhq6vLU/b000+zcOFCPve5zwFw3XXXsXDhQl577bVxH98fI6P9icvl4oMPPhDOG8R1F9UbxHUX1RvEddett6sHRvo3XFWhogD12J+huxk1KBzmfgzm3X4haIG+CeUMFxY41Am6bXMv8IezMIFLTEwMW7duxW6309bWxrPPPkt4eLjn9YyMDFRVZfXq1Z6yxx9/HFVVhzzGGlczHP5YKMqfuN1uKioqhPMGcd1F9QZx3UX1BnHddettMMFwc525nHD6X1D2FgbgXOwqlMX3aas5Dzs5mqrdPtIRum1zL5CLLEokEolEMhxB4VrPiqpeCEh67HDqZW2lZYMRV9YGjto+RYr5NAwzeBdXrxYABYVOqrpkfMjARSKRSCTik3A5hERAdwuExkB7DZz6B/R2gDkE5t6KOyoT7KPsw14LkSnaTLoS3SIDFy8RbTS30WgkOztbOG8Q111UbxDXXVRvENddt94RKZA0HyoKoKMWzuSDW9Gm+593G1ijMaoq2UENGIcbDKOq0NMOl98MlpDJ9x8F3ba5F0zrrKJAIbOKJBKJRBCqj8Cr90ND32SlMVlw+S1gHjo31xDaz2tjZNY8Cjbfzg82nZnWWUWB5uLZAPWOoijs379fOG8Q111UbxDXXVRvENddt949dtj3kwtBS8rVWk/LgKBFUQ3s70xDUS8alNvZqN1SyrlZl0GLbtvcC/zhLG8VeYloHVOqqtLQ0CCcN4jrLqo3iOsuqjeI665L75Zy+POdUP8hmILhio+Bs0sLSMLioG/6fxUDDa5wVAyAqt1Kaq8BpVu7RTR7fSBrMSK6bHMv8YezDFwkEolEIi7l78Bf/wu6miA8Ef5jKyRdCaf+CeVva8FMkK0vgAnS3tNjh84aLYsoPBGuvA1mrQEBx5BMR2TgIpFIJBIxOfwc5P8/reckeYEWtETO0F676pOQtQbOH4Gyt6GzXsuAtlwFjlaImwPp10LyVVo2kkQYZODiJcMtVqVnTCYTCxYsEM4bxHUX1RvEdRfVG8R114W3S4Ht34KD/6v9Pu82uOVXQ+dfCY+Hy26AWauhox5TbzcLGtowpXxTS3s2itH2umjzCeIPZ5lVNAYyq0gikUh0RFcz/P1uOLtX+33tt2Hl/xthFlxJoJFZRQFEtNHciqKwe/du4bxBXHdRvUFcd1G9QVz3gHo3FMH/rdOCFksY3PEnuO7rXgctss0nH5lVFEBE65hSVRW73S6cN4jrLqo3iOsuqjeI6x4w7+Kd8Pd7tEniItPgzj9D0rxx7UK2+eQjs4okEolEMr1QVSj4Nez8DqhuSFsOd/xRyxKSTEtk4CKRSCQSfaL0wOtfhaMvar9f/V+Q91MwBwXWSxJQ5ODcMegfWNTS0kJUVFSgdbzG7XbT2NhIXFyccOtbiOouqjeI6y6qN4jrPmneHfXw0qeh8oA2gdwNW2Dp5y9pEK5s88mntbWV6Ohonw7OlYHLGMisIsm04PxRbQKv0BgwmsFg0lJFjWbtomE09ZWZ+54bBzwfuO0kZ3aoqjZDalDY5B5X4l9qjsGfPwXtVRASCZ/4A2StDbSVZAL44xoqbxV5idPpDLTCuHA6nezYsYMNGzZgsVgCrTMuRHUX1Zv6QtTfX4/B5YvvuGFAEGMaIcgxazOUDgp4TFrZeIImgxF3SzmVPeHMyLoS88qvaPN2CIKo3xe/e596FV79ghaQxs6GO1+CuNk+2bVs88nHH9dOGbhMYURMnetHVHchvavex+By4jJYMIbHY1Bd4HZB/0/Pc0V7zmidtH3rv7gnpx2MQDpA41448EttFtSsdTB7HcxcovuxEEJ+X/CTt9sN+34Me7dov2etg9ufBWuUTw8j21x8ZOAikUx3qg4AUBZ/Pemf++PY/9Gpal9AowwIbhQt4+PiIEd1D3jeX+6+6H0XB0jDbasMDabcCq6ak5yta2W2UoShuVS7xVBzDN75HwgKh8zrtFsMs9dBzKxJaEzJhOjt1HpZPvyn9vuyL8L674FJXqIkQ5HfColkulO2D4CG8Lla78VYGAzaBUUHFxW308mH+flk5OVhcTTD2T1QsgtKd0NXI5zJ1x4A0ZlaAJO1Vgtogm2BlZdotFbCXz4FtcfBaIGbfwZX/2egrSQ6Rg7OHYP+gUWtra1ERkYGWsdr+icsstlsGASbCltUdyG9WyvgqStRDSbsXzyJLTZZHHdGaXO3W7sQlu6Ckt1Q+d7g21dGM6QuvdAbk3TVpK8MLOT3BR97VxyAlzZBZwOExmkz4abn+kZ0GGSbTz5tbW1ERUXJwbkS77BarYFWmDCiugvnXfa29nPGIqyR4gxsHciwbW40QsoC7bHyIeixa3Ut3aX1yLSUwbl3tcfu72sXzaw12riKrLVgSwycuwD4xPvoVvjXV8DVC4lXwp1bISrt0vc7BtO6zacIYiWEBxDRBkYpikJ+fr5w3iCuu5DefbeJ3GnXiufOONo82AY5ebDxp/CVo/DlDyDvScjeqI2F6WqEE3+DV++Hn14Gv10BO76jrYmj9ATWXWdcsrfbBdsf1ca0uHrh8o/APdsmJWiZtm0eQORaRRKJxHeoqidwUTNWQmFHgIUmkZhZsGQWLPkcuJxQefBCb0zNUag7oT32/wIsoZCx4kK2UuxsuRLxRHG0wd/vhZKd2u+rvgmrHp7023QSsZGBi0QyXWk+C/bzYApCnXkNFO4JtFFgMFkg41rtse670NkIpXu0QKZ0N3TUQfEO7QHaAn+z12qBzKxV2gRpkrFpKoU//wc0FoHZCrf+Fq64NdBWEgGRgYtEMl0pe0v7mboULPL+uYewOJj/Ce2hqlB3si9TaRdUvAdtFfD+H7SHwQQzr+nLVlqnjakxmgJcAR1ydi/89TPgaIWIGfAfW7W2kkgmgMwqGgORs4oURcFsNgs3Cl1Ud+G8/3YXnHoFVn8LddU3xHLvY9LbvLcTyt+9cFupqXjw69ZomLX6wm2liJQRdyXc96WPcXmrKhz8HWx7WJuDZ+Y1cMeLkzb4eajONGhznSGziiTjoru7G5tNzLkqRHUXxltVL2QUZV4HCOR+EZPqHRQGl23QHgAt57TbSaW74Ow+6G7RgsFTr2ivx19+Ye6Y9OUXerbaa6DhDN1OA7a0+RAaPTn+PsKrNld64d9f13qmAK66E25+Ciwh/tYbFfk9Fx85IspLRBvNrSgKe/bsEc4bxHUXyru+UMuksYTCjEViuQ8g4N7R6bD4bm3+kW+chXu2w3XfgBmLAAM0FELBr+BPH4cnMuCPH4c3H4cd30Y5+Cx7zrSi7P81dDYFxn8CeNXmnU3wx1v7ghYDrP8+fOy3AQ9aAv59mSCieoPMKpJIJL6iL5uItFxtPR/BFhHVJSYzpC3THmsfha7+mXz7emTsNX0DfncBYA6ysTi0BqOxFXpbYd4ntIyl0Bixs5bqTmmDcFsrIDgCbvv9hR4qicQHyMBFIpmO9AcumSsD6zGVCY2BebdpD1WFhtPauJiD/wttVRh67czoPahte7BIGwsCWpZSTJYWxMRm9T3ve+g9g+l0Prz8Oejt0JZYuPMvkJATaCvJFEMGLlMYs1ncj1dUdyG83S4of0d73je+BQRxHwYhvA0GSLhce4TGwof/RFGNFHWGkd19GFNwOHQ1QXu1NtfJ+SPa42JC4wYENLMGPw8Km7TqDGlzVdUWttz1fUDVvlefeF4L3nSGEN+XYRDV2x/IrKIx6M8q8uWIaIkkoJz/AJ5ZDcGR2rgMHSyWOK3o6YBjf4aa49rEa5nXweUf1T6H3i5tOYKmEm3ek+ZS7WdTKXTWj75fW8owAU0WxGSCOfjSvZ3dmvP5I9DTDmGJMONqrWflja9qMw8DXPM5uHGLNj+OZNrjj2uoPGN5idvtDrTCuHC73TQ2NhIXF4dRsFkpRXUXxrv/NlHGtZ6gRRj3ixDSOzgcrvks7q5WGlvaiEtJu+AeFAqJV2iPi3G0Xwhkms/2BTQlWll3izaZoP08lL89+H0GI0TOHHDLafaF51Fp3gUYXc1w+PdQcwK3wUSjOYW4ug8xFm3X5rlpq9AWrsz7CSy+59LbyE8I+X1BXG/wz7VTBi5e4nK5Aq0wLlwuFwUFBeTl5Qn3RRfVXRhvT+ByYXyLMO4XIao3BgOuoHAK3t9HXuIM79xDIiBlofa4mK7mi3po+gKaprPQa9cGyrZWaIOFB2I0Q1T6gIBm1oXnETO1HiFV1RZEPH8UYmfjMoVSYM9ho6kDY/HfwNmprfd05190P2ZK1O+LqN7gn2unDFwkkumEywnnCrTnA8a3SAQnNEZ7pF4zuFxVoaN+QE9NX1DTdFbrtVG6tbLm0gtLGvRjCtZuM9mStYyo8ERtXyGxzGjej6nyT+BWtAHDl900fEAlkfgBGbhIJNOJ6iPaf8ihsZAwN9A2En9jMGiz1NoStQnwBuJ2a7eWLh5L01wKzWXg6tEyoRpOa9v3/bQAi/v3ETsb5tyg7aetUht8LJH4GRm4eIlo0ywbDAZsNptw3iCuuxDeA28TDehyFsJ9GET1Bh24G/vGvkTO1BaLHIhL0QKR5lItxbl0N2CA7mZURxsqBkhdijFzJahurWdH1f84wIC3+QQR1Rv8c+2UWUVjILOKJFOKP9ysDd7c+FO45rOBtpGIQH0h7HtSu2UUFKal07uVC5lKHXVa4HL9Y7pMf5YEFn9cQ8Ua5RNARMwqOnfunHDeIK677r2dDqjsm/Asc/B/2Lp3HwFRvUEg97jLtEfrOXC7cBtMnHMn4lYBxQGdDZC6RIigRZg2vwhRvcE/104ZuHiJiFlFR48eFc4bxHXXvXfVQW3cgi1ZG5swAN27j4Co3iCQu9EECz4F0RnQUIirrZqjjhRcLRXaraSUhXD5zYG29Aph2vwiRPUGmVUkkUguBc80/9eJvRaOZPKJSoVrvwIV78G5A9CDNjYmMxdmLtHmppFIJglhelyam5vZtGkTERERREVFce+999LR0THq9g888ADZ2dlYrVbS0tL48pe/TFtb2yRaSyQ6YmDgIpGMl7A4rWdl7Xe036/7OmStlUGLZNIRJnDZtGkTp06dYufOnbz++uvs27eP++67b8Ttz58/z/nz53nyySc5efIkf/jDH9i2bRv33nvvhI4v2mhug8FAfHy8cN4grruuvXvsUP2+9jxj6CRhunYfBVG9QVx3g9GoeQs2ERoI3OaCesM0zioqLCxk7ty5HDp0iMWLtRkEtm3bRl5eHlVVVaSkpHi1n7/97W98+tOfprOz0+sFq2RWkWRKULwTXrxdmyX1weOBtpFIJNOEabtWUUFBAVFRUZ6gBeD666/HaDRy4MABbr31Vq/2099wowUtPT099PT0eH5vb28HwOFwYLVaATAajZhMJlwu16AR0/3liqIwMB40mUwYjcYRy51O5yCHfj9FUbwqt1gsuN3uQYOg3G43ZWVlZGVlDdrWYDBgNptHdNdDnVwuF+Xl5SO6X1xXvdTJ5XJRWlpKdna2Z/8DGe5zmqw6uc++hRFwp6/A5XQOqdNY7uP57k3m56QoCqWlpWRlZREUFOS3vyd/1Gk498k8R0y0Tr29vRQXF5OVleXx08t5b6w6jeSuh/PeaHUyGAwUFRWRmZmJyWQaVKdAn/fGKp+2g3Nra2tJSEgYVGY2m4mJiaG2ttarfTQ2NvL9739/1NtLAFu2bGHz5s1Dynft2kVoaCgAaWlpLFy4kOPHj1NRUeHZJjs7m5ycHA4ePEhDQ4OnfMGCBaSnp7Nv3z7sdrunPDc3l4SEBHbs2DHow16zZg1Wq5X8/PxBDnl5eXR3d7Nnz4X1RsxmMxs3bqSxsZGCggJPeXh4OB0dHQQFBXHixAlPeXx8PMuXL6e4uJgzZ854yvVWJ0VRiIiI4NChQ55ym83G2rVrqays5OjRo7qtU2ZmJoqiePU5TVadOk7kEwEcabVRnZ8/Yp2Sk5Ox2WyX9N0LxOdUUlLi178nf9appKQkIOeIidbpxIkTVFVVUVJSMu7PSQ91Kikp8bjr7bw3Up1WrlxJUVERRUVFXn9OeqnTsmXL8DUBvVX08MMP88QTT4y6TWFhIS+//DLPP//8oA8HICEhgc2bN/OFL3xh1H20t7ezfv16YmJieO2117BYRl4Ndbgel9TUVGpqaoiNjQX0F9EOF6UrisKOHTu48cYbBy3KJUKU7nQ62blz54jueu1x6fe+6aabsFgs+umd6GlDfSITAyrOL58EW9KQOo3lHujeiZE+p97eXnbu3Mn69esJCQnRXe/EaHUazl1PvRMjuTscDrZv38769euxWCy6Ou+NVaeR3PVw3hutTqqqkp+f7/EeWKdAn/fGKm9vbycuLm7q3Cp66KGHuOuuu0bdZtasWSQlJVFfXz+oXFEUmpubSUpKGvX9drudG2+8EZvNxiuvvDJq0AIQHBxMcHDwkHKLxTLkvSaTydNtN5CRbkWNVD6S03jKjUbjsKuGGo3GYbcfyV1vdRpPXfVSp/6u3fF+Tn6rU/m7GFAh7jIsMakTdh9u+9HcJ+Nz6j/R9l+ERnIcb/lk1Gk490CdI8Zbp/5jDDyO3s57I9Wpf18D96e3897F7v3Bw3iuQ3qqk68JaOASHx9PfHz8mNvl5ubS2trK+++/z6JFiwDYvXs3brebpUuXjvi+9vZ2brjhBoKDg3nttdcICQmZsKtoS4kbjUbS0tKE8wZx3XXrXf629nOUNGjduo+BqN4grruo3iCuu6je4J9rpxBZRQA33XQTdXV1PP300zidTu6++24WL17M1q1bAaiurmbdunW88MILLFmyhPb2djZs2EBXVxevvPIKYWFhnn3Fx8cPG4kOh8wqkgjPb3Kh/kP45Asw96OBtpFIJNOIab1W0YsvvkhOTg7r1q0jLy+PFStW8Mwzz3hedzqdnDlzhq6uLgCOHDnCgQMHOHHiBLNnzyY5OdnzqKysHPfxRZtq2eVy8cEHHwjnDeK669K7o14LWgDSV4y4mS7dvUBUbxDXXVRvENddVG/wz7VTmMAlJiaGrVu3YrfbaWtr49lnnyU8/MKMjRkZGaiqyurVqwFYvXo1qqoO+8jIyBj38UVb3MrtdlNRUSGcN4jrrkvv/ttEiVdCWOyIm+nS3QtE9QZx3UX1BnHdRfUGuciiRCIZL2Vjj2+RSCQSkZCBi0QylZHrE0kkkimGDFy8RLTR3EajkezsbOG8QVx33Xm3VUFzKRiMkJ476qa6c/cSUb1BXHdRvUFcd1G9YZpnFQUKmVUkEZajf4ZX74cZi+BzuwNtI5FIpiHTOqso0Fw8G6DeURSF/fv3C+cN4rrrztuL+Vv60Z27l4jqDeK6i+oN4rqL6g3+uXbKwMVLROuYUlWVhoYG4bxBXHddeavquMa36Mp9HIjqDeK6i+oN4rqL6g3+uXbKwEUimYq0lEFbJRgtkOr7Rc4kEokkUMjARSKZivT3tsy8BoJCA+sikUgkPkQGLl7i7RIBesFkMrFgwQLhvEFcd115j3P+Fl25jwNRvUFcd1G9QVx3Ub3BP9dOmVU0BjKrSCIcqgpPXgad9XBXPmRcG2gjiUQyTZFZRQFEtNHciqKwe/du4bxBXHfdeDec0YIWsxVmLvbqLbpxHyeieoO47qJ6g7juonqDzCoKKKJ1TKmqit1uF84bxHXXjXf/+Ja0pWAO9uotunEfJ6J6g7juonqDuO6ieoPMKpJIJN5QLqf5l0gkUxcZuEgkUwm3e8DA3FWBdZFIJBI/IAMXLxFtNLfJZCI3N1c4bxDXXRfedSfA0QpBNkhe4PXbdOE+AUT1BnHdRfUGcd1F9Qb/XDvNPt/jFEW0xa2MRiMJCQmB1pgQorrrwrt/fEv6cjB5/+etC/cJIKo3iOsuqjeI6y6qN/jn2inW1TiAOJ3OQCuMC6fTyRtvvCGcN4jrrgvvcUzzPxBduE8AUb1BXHdRvUFcd1G9wT/XThm4TGFETJ3rR1T3gHq7nHBuv/Z8AgNzZZtPPqK6i+oN4rqL6u0PZOAikUwVzh+F3g6wRkPivEDbSCQSiV+QgYtEMlUoe0v7mbECBBuTJZFIJN4ip/wfg/7piltbW4mMjAy0jtf0T1hks9kwGAyB1hkXoroH3Pv5W7TgJe9JWPK5cb014O4TRFRvENddVG8Q111Ub4C2tjaioqLklP8S77BarYFWmDCiugfMW+mBygPa8wlOPCfbfPIR1V1UbxDXXVRvfyADFy8RbWCUoijk5+cL5w3iugfUu+oQKA4IT4S4y8b9dtnmk4+o7qJ6g7juonqDXKtIIpGMRH8adMZKEKwrWSKRSMaDDFwkkqnABOdvkUgkEtGQgYtEIjq9nVB1WHsuAxeJRDLFkVlFYyByVpGiKJjNZuFGoYvqHjDvkl3wp49DZBo8eHxCt4pkm08+orqL6g3iuovqDTKrSDJOuru7A60wYUR1D4i35zbRpY1vkW0++YjqLqo3iOsuqrc/kIGLl4g2mltRFPbs2SOcN4jrHjBvH4xvkW0++YjqLqo3iOsuqjfIrCKJRHIxjjaoOao9z1gZUBWJRCKZDGTgIpGIzLn9oLohdjZEzgi0jUQikfgdGbhMYcxmc6AVJoyo7pPuPXD+lktEtvnkI6q7qN4grruo3v5AZhWNQX9WkS9HREskPuO310LdSbj9OZj38UDbSCQSySD8cQ2VPS5e4na7A60wLtxuN/X19cJ5g7juk+7d2aQFLXDJPS6yzScfUd1F9QZx3UX1Bv9cO2Xg4iUulyvQCuPC5XJRUFAgnDeI6z7p3uVvaz8TroDw+EvalWzzyUdUd1G9QVx3Ub3BP9dOGbhIJKIip/mXSCTTEBm4SCSiMnDiOYlEIpkmyMDFS0SbZtlgMGCz2YTzBnHdJ9W7vQaaisFghPRrL3l3ss0nH1HdRfUGcd1F9Qb/XDtlVtEYyKwiiS45/ld4+XOQshDu2xtoG4lEIhkWmVUUQEQbze12uzl37pxw3iCu+6R6l72l/fTR+BbZ5pOPqO6ieoO47qJ6g8wqCiiijeZ2uVwcPXpUOG8Q131SvT0Tz/kmcJFtPvmI6i6qN4jrLqo3yKwiiUQC0FIOrRVgNEPaskDbSCQSyaQiTODS3NzMpk2biIiIICoqinvvvZeOjo5R3/P5z3+erKwsrFYr8fHxfPSjH+X06dOTZCyR+ImyvvlbZiyG4PDAukgkEskkI0zgsmnTJk6dOsXOnTt5/fXX2bdvH/fdd9+o71m0aBHPPfcchYWFbN++HVVV2bBhw4S6rkQbzW0wGIiPjxfOG8R1nzRvP8zfItt88hHVXVRvENddVG+YxllFhYWFzJ07l0OHDrF48WIAtm3bRl5eHlVVVaSkpHi1n+PHj3PVVVdRUlJCVlaWV++RWUUSXaGq8NMc6KiFz/xLTj4nkUh0jT+uoUIsN1lQUEBUVJQnaAG4/vrrMRqNHDhwgFtvvXXMfXR2dvLcc8+RmZlJamrqiNv19PTQ09Pj+b29vR0Ah8OB1WoFwGg0YjKZcLlcg0ZM95crisLAeNBkMmE0Gkcsdzqdgxz6VwFVFMWrcovFgtvtHtST5Ha7KSsrGxKgGQwGzGbziO56qJPL5aK8vHxE94vrqpc6uVwuSktLyc7O9ux/IMN9TuOuU3MJpo5aVFMwStJC6HO61DqN5T6e795kfk6KolBaWkpWVhZBQUF++3vyR52Gc5/Mc8RE69Tb20txcTFZWVkeP72c98aq00juejjvjVYng8FAUVERmZmZmEymQXUK9HlvrHJ/DM4VInCpra0lISFhUJnZbCYmJoba2tpR3/ub3/yGb3zjG3R2dpKdnc3OnTsJCgoacfstW7awefPmIeW7du0iNDQUgLS0NBYuXMjx48epqKjwbJOdnU1OTg4HDx6koaHBU75gwQLS09PZt28fdrvdU56bm0tCQgI7duwY9GGvWbMGq9VKfn7+IIe8vDy6u7vZs2fPoHbYuHEjjY2NFBQUeMrDw8Pp6OggKCiIEydOeMrj4+NZvnw5xcXFnDlzxlOutzopikJERASHDh3ylNtsNtauXUtlZSVHjx7VbZ0yMzNRFMWrz2m8dbra9QGpQEf0FezesdvndUpOTsZms13Sdy8Qn1NJSYlf/578WaeSkpKAnCMmWqcTJ05QVVVFSUnJuD8nPdSppKTE4663895IdVq5ciVFRUUUFRV5/TnppU7Llvk+gSCgt4oefvhhnnjiiVG3KSws5OWXX+b5558f9OEAJCQksHnzZr7whS+M+P62tjbq6+upqanhySefpLq6mnfffZeQkJBhtx+uxyU1NZWamhpiY2MB/UW0w0XpiqKwY8cObrzxRozGC0OZRIjSnU4nO3fuHNFdrz0u/d433XQTFovFL//1ml++B0Pha7hXP4rr2q/6rE5juQe6d2KkOvX29rJz507Wr19PSEiI7nonRqvTcO566p0Yyd3hcLB9+3bWr1+PxWLR1XlvrDqN5K6H895odVJVlfz8fI/3wDoF+rw3Vnl7eztxcXFT51bRQw89xF133TXqNrNmzSIpKYn6+vpB5Yqi0NzcTFJS0qjvj4yMJDIykjlz5rBs2TKio6N55ZVXuPPOO4fdPjg4mODg4CHlFovF84Xpx2QyebrtBtL/AXpbfvF+J1JuNBoHXeQHlg+3/UjueqvTeOqqlzr1d+2O93Mas05uN5S/o20/axXGYfZ/qXUazX247Udzn4zPqf9E238RGslxvOWTUafh3AN1jhhvnfqPMfA4ejvvjVSn/n0N3J/eznsXu/cHD+O5DumpTr4moIFLfHw88fHxY26Xm5tLa2sr77//PosWLQJg9+7duN1uli5d6vXxVFVFVdVBPSreMtwfgZ4xGo2kpaUJ5w3iuvvdu/4UdDeDJQxmXO3TXcs2n3xEdRfVG8R1F9Ub/HPtFCKrCOCmm26irq6Op59+GqfTyd13383ixYvZunUrANXV1axbt44XXniBJUuWcPbsWV566SU2bNhAfHw8VVVV/OhHP+Ldd9+lsLBwyJiZkZBZRRLdUPAb2P4IzF4Pn/57oG0kEolkTKb1WkUvvvgiOTk5rFu3jry8PFasWMEzzzzjed3pdHLmzBm6uroACAkJ4e233yYvL4/Zs2dzxx13YLPZ2L9/v9dBy0BEm2rZ5XLxwQcfCOcN4rr73dsP87f0I9t88hHVXVRvENddVG+Y5lP+x8TEsHXrVux2O21tbTz77LOEh1+YNTQjIwNVVVm9ejUAKSkp5OfnU1dXR29vL5WVlbz44otkZ2dP6PiiLW7ldrupqKgQzhvEdfert0uBc+9qzzNX+nz3ss0nH1HdRfUGcd1F9QadLLKYn5/P9u3bh5Rv376df//73z6RkkgkF1FzDHraISQSkuYH2kYikUgCxrgDl4cffnjYrh9VVXn44Yd9IiWRSC6ivH816JVgHJopIJFIJNOFcQcuxcXFzJ07d0h5Tk6OZ1KfqYhoo7mNRiPZ2dnCeYO47n719uP4FpBtHghEdRfVG8R1F9Ub/HPtHPceIyMjOXv27JDykpISwsLCfCKlR4bLh9czJpOJnJwc4bxBXHe/eSu9cK5vJk0/BS6yzScfUd1F9QZx3UX1Bv9cO8cduHz0ox/lwQcfpLS01FNWUlLCQw89xC233OJTOT1x8WyAekdRFPbv3y+cN4jr7jfv6sOgdENYPMTn+Hbffcg2n3xEdRfVG8R1F9Ub/HPtHHfg8uMf/5iwsDBycnLIzMwkMzOTyy+/nNjYWJ588kmfC+oFQaa78aCqKg0NDcJ5g7jufvMue1v7mbES/LSsvWzzyUdUd1G9QVx3Ub3BP9fOcc+cGxkZyf79+9m5cyfHjh3DarUyf/58rrvOP13YEsm0x8/jWyQSiUQkJjTlv8FgYMOGDWzYsMHXPhKJZCC9XVB1UHsuAxeJRCLxLnD5xS9+wX333UdISAi/+MUvRt32y1/+sk/E9IZog6JMJhMLFiwQzhvEdfeLd+UBcPVCxAyImeW7/V6EbPPJR1R3Ub1BXHdRvcE/106v1irKzMzk8OHDxMbGkpmZOfLODIZhM45ERq5VJAkou74Hb/8UrroTbn060DYSiUQyLgK2VlFZWRmxsbGe5yM9plrQMhDRRnMrisLu3buF8wZx3f3iPUnjW2SbTz6iuovqDeK6i+oNOsgqcjqdZGVlUVhY6HMRvSPaaG5VVbHb7cJ5g7juPvd2tEP1Ee15hu/XJxqIbPPJR1R3Ub1BXHdRvcE/185xBS4WiwWHw+FzCYlEMgwVBaC6IDoTolIDbSORSCS6YNzzuHzxi1/kiSeeELLLSiIRCpkGLZFIJEMYdzr0oUOH2LVrFzt27ODKK68cMs3/yy+/7DM5PSHaaG6TyURubq5w3iCuu8+9JzFwkW0++YjqLqo3iOsuqjf459o57sAlKiqK2267zecieke0xa2MRiMJCQmB1pgQorr71LurGWpPaM8nIXCRbT75iOouqjeI6y6qN/jn2jnuwOW5557zuYQIOJ3OQCuMC6fTyY4dO9iwYQMWiyXQOuNCVHefepe/A6ja2kTh/j9hyTaffER1F9UbxHUX1Rv8c+0cdyi0du1aWltbh5S3t7ezdu1aXzhJfITI45BEdfeZdwDGt0z7Ng8AorqL6g3iuovq7Q/GHbjs3buX3t7eIeUOh4O3337bJ1ISybSnvO9vSQ7MlUgkkkF4favo+PHjnucffvghtbW1nt9dLhfbtm1jxowZvrWTSKYj9jpoOA0YIP3aQNtIJBKJrvBqyn/QBtgYDAZg+AllrFYrv/zlL7nnnnt8axhg+qcrbm1tJTIyMtA6XtM/YZHNZvN8bqIgqrvPvE/8Hf5xLyTNh/snpxdz2rd5ABDVXVRvENddVG+AtrY2oqKifDrlv9c9LmVlZaiqyqxZszh48CDx8fGe14KCgkhISBAyVWsqY7VaA60wYUR194l32Vvaz0m+TTSt2zxAiOouqjeI6y6qtz/weoxLeno6GRkZuN1uFi9eTHp6uueRnJw85YMW0QZGKYpCfn6+cN4grrvPvMv6x7esunQpL5n2bR4ARHUX1RvEdRfVG3SwVlE/f/zjH7n22mtJSUnh3LlzAPzsZz/jn//8p0/lJJJpR2sFtJSBwQTpuYG2kUgkEt0x7sDlt7/9LV/72tfIy8ujtbUVl8sFQHR0NE899ZSv/SSS6UV/b8uMRRBsC6yLRCKR6JBxBy6//OUv+d3vfsejjz466PbQ4sWLOXHihE/lJJJph2f+Fv+uBi2RSCSi4nVWUT9Wq5XTp0+Tnp6OzWbj2LFjzJo1i+LiYubPn093d7e/XAOCyFlFiqJgNpuFG4Uuqvsle6sq/OwKaK+G//onzFrtc8eRDz1N2zyAiOouqjeI6y6qN/gnq2jcPS6ZmZkcPXp0SPm2bdu4/PLLfeEk8REiB5Giul+Sd/NZLWgxBUHqUt9Jecm0bPMAI6q7qN4grruo3v5g3IHL1772Nb74xS/y0ksvoaoqBw8e5Ac/+AGPPPII3/jGN/zhqAtEG82tKAp79uwRzhvEdb9k7/406NSlYJnc1Mdp2+YBRFR3Ub1BXHdRvcE/185xL7L42c9+FqvVyre//W26urr41Kc+RUpKCj//+c/5j//4D58LSiTThv7xLRlyfItEIpGMxLgDF4BNmzaxadMmurq66OjoEHa5bYlEN6jqgPlb5PpEEolEMhITClz6CQ0NJTQ01FcuEh9jNl/SxxtQRHWfsHd9IXQ1giVUS4UOANOuzXWAqO6ieoO47qJ6+wOvs4rWrl3r1Q537959SUJ6oz+ryJcjoiWSIbz3NGz7JmStg/98OdA2EolE4hP8cQ31OoTbu3cv6enpbNy4EYvF4pODi4Tb7Q60wrhwu900NjYSFxeH0TihCZIDhqjul+Qd4PlbpmWbBxhR3UX1BnHdRfUG/1w7vW6BJ554AqvVyt/+9jcMBgP33nsvP/vZz4Y8pir9MwSLgsvloqCgQDhvENd9wt5uF5x7R3seoPEt067NdYCo7qJ6g7juonqDf66dXgcuX//61/nwww959dVXsdvtXHvttSxZsoSnn36a9vZ2n4tJJNOG2uPgaIPgSEi6KtA2EolEomvG3eeUm5vL7373O2pqavjiF7/Is88+S0pKigxeJJKJ4kmDvhZMcgCeRCKRjMaEb5YdOXKEt956i8LCQubNmzflx72INs2ywWDAZrMJ5w3iuk/YWwfzt0y7NtcBorqL6g3iuovqDf65do5rraLz58/zhz/8gT/84Q+0t7fz6U9/mnvuuYe5c+f6XEwvyKwiiV9xOeFH6eDshPvfhaR5gTaSSCQSn+GPa6jXPS55eXlkZWVx4MABfvKTn1BVVcWTTz45pYOWgYiYVXTu3DnhvEFc9wl5Vx/RgpbQWEgI3N/StGpznSCqu6jeIK67qN4Q4Kyibdu2ERMTQ0VFBZs3b2bJkiVcffXVQx5TFdFGc7tcLo4ePSqcN4jrPiHvgbeJApjmOK3aXCeI6i6qN4jrLqo3+Ofa6fVIwMcee8znB5dIpj39CysGaP4WiUQiEQ1hApfm5mYeeOAB/vWvf2E0Grntttv4+c9/Tnh4+JjvVVWVvLw8tm3bxiuvvMLHPvYx/wtLJGPhdEDlQe155qrAukgkEokgCDMF36ZNmzh16hQ7d+7k9ddfZ9++fdx3331evfepp5665JHNoo3mNhgMxMfHC+cN4rqP27vqILh6wJYMsbP9KzcG06bNdYSo7qJ6g7juonqDDrKKAkVhYSFz587l0KFDLF68GNDG3OTl5VFVVUVKSsqI7z169Cg333wzhw8fJjk5edw9LjKrSOI3dv9/sO8nMP8O+PgzgbaRSCQSnxPQtYoCSUFBAVFRUZ6gBeD666/HaDRy4MABbr311mHf19XVxac+9Sl+/etfk5SU5NWxenp66Onp8fzeP7Gew+HAarUCYDQaMZlMuFyuQSOm+8sVRWFgPGgymTAajSOWO53OQQ79q4AqiuJVucViwe12DxoE5Xa7KSsrIysra9C2BoMBs9k8orse6uRyuSgvLx/R/eK66qVOLpeL0tJSsrOzPfsfyMWfk+nsW1qXZ+Z1Aa/TWO7j+e5N5uekKAqlpaVkZWURFBTkt78nf9RpOPfJPEdMtE69vb0UFxeTlZXl8dPLeW+sOo3krofz3mh1MhgMFBUVkZmZiclkGlSnQJ/3xioP6ODcQFJbW0tCQsKgMrPZTExMDLW1tSO+76tf/SrLly/nox/9qNfH2rJlC5s3bx5SvmvXLkJDQwFIS0tj4cKFHD9+nIqKCs822dnZ5OTkcPDgQRoaGjzlCxYsID09nX379mG32z3lubm5JCQksGPHjkEf9po1a7BareTn5w9yyMvLo7u7mz179gxqh40bN9LY2EhBQYGnPDw8nI6ODoKCgjhx4oSnPD4+nuXLl1NcXMyZM2c85Xqrk6IoREREcOjQIU+5zWZj7dq1VFZWcvToUd3WKTMzE0VRRv2cTC4HeVXvay9mrNRNnZKTk7HZbJf03QvE51RSUuLXvyd/1qmkpCQg54iJ1unEiRNUVVVRUlIy7s9JD3UqKSnxuOvtvDdSnVauXElRURFFRUVef056qdOyZcvwNV7fKiorKyMzM9OnB3/44Yd54oknRt2msLCQl19+meeff37QhwOQkJDA5s2b+cIXvjDkfa+99hoPPfQQH3zwgWcAr8FgGPNW0XA9LqmpqdTU1BAbGwvoL6IdLkpXFIUdO3Zw4403DlpNVIQo3el0snPnzhHdA907MZJ7v/dNN92ExWIZ9XMylO7C/Jc7UKPSMTx4POB1Gss90L0TI9Wpt7eXnTt3sn79ekJCQnTXOzFanYZz11PvxEjuDoeD7du3s379eiwWi67Oe2PVaSR3PZz3RquTqqrk5+d7vAfWKdDnvbHK29vbiYuLC8ytoqysLNLT01mzZo3nMXPmzEs6+EMPPcRdd9016jazZs0iKSmJ+vr6QeWKotDc3DziLaDdu3dTWlpKVFTUoPLbbruNlStXsnfv3mHfFxwcTHBw8JByi8UyZFkDk8nk6bYbSP8H6G35SMsljKfcaDQOu9y50WgcdvuR3PVWp/HUVS916u/aHdW94l1t277VoPVSp9Hch9t+NPfJqFP/ibb/IjSS43jLJ6NOw7kH6hwx3jr1H2PgcfR23hupTv37Grg/vZ33LnbvDx7Gcx3SU518jdeBy+7du9m7dy979+7lz3/+M729vcyaNYu1a9d6ApnExMRxHTw+Pp74+Pgxt8vNzaW1tZX333+fRYsWeXzcbjdLly4d9j0PP/wwn/3sZweVXXnllfzsZz/jIx/5yLg8gWH/CPSM0WgkLS1NOG8Q131c3v0Tz+kkDXpatLnOENVdVG8Q111Ub/DPtXNCWUUOh4P9+/d7ApmDBw/idDrJycnh1KlTPpcEuOmmm6irq+Ppp5/G6XRy9913s3jxYrZu3QpAdXU169at44UXXmDJkiXD7sObW0UXI7OKJD6nuwWeyARUeOgM2LwbOC6RSCSiEdC1igYSEhLC2rVr+fa3v83mzZv58pe/THh4OKdPn/aJ1HC8+OKL5OTksG7dOvLy8lixYgXPPHMhhdTpdHLmzBm6urr8cnzRplp2uVx88MEHwnmDuO5ee5/bD6gQd5lugpYp3+Y6RFR3Ub1BXHdRvcE/185xBS69vb3s27ePzZs3s2bNGqKiorj//vtpaWnhV7/6FWVlZT4X7CcmJoatW7dit9tpa2vj2WefHTRrbkZGBqqqsnr16hH3oarqhGfNFW1xK7fbTUVFhXDeIK67196e20TX+V/KS6Z8m+sQUd1F9QZx3UX1Bv9cO70e47J27VoOHDhAZmYmq1at4vOf/zxbt24lOTnZ51ISyZRGh4GLRCKRiILXgcvbb79NcnIya9euZfXq1axatcqTHiyRSLykowHqP9Sep68IrItEIpEIiNe3ilpbW3nmmWcIDQ3liSeeICUlhSuvvJIvfelL/P3vfx80oc1URLTR3EajkezsbOG8QVx3r7zL39Z+Jl4JYfoJ/Kd0m+sUUd1F9QZx3UX1Bh1lFQHY7Xbeeecd9uzZw969ezl27Bhz5szh5MmTvnYMKDKrSOJT/vUgvP8cLPsi3PjDQNtIJBKJX9FNVhFAWFgYMTExxMTEEB0djdlsprCw0CdSeuTi2QD1jqIo7N+/XzhvENfdK2+djm+Z0m2uU0R1F9UbxHUX1Rv8c+30eoyL2+3m8OHD7N27lz179vDuu+/S2dnJjBkzWLNmDb/+9a9Zs2aNzwX1ggCLaA9CVVUaGhqE8wZx3cf0bquG5lIwGCE9d3LlxmDKtrmOEdVdVG8Q111Ub/DPtdPrwCUqKorOzk6SkpJYs2YNP/vZz1i9evWQFXwlEskI9I9vSVkIIZGBdZFIJBJB8Tpw+clPfsKaNWu47LLL/OkjkUxddHqbSCKRSETC6zEun//854cELVdeeSWVlZU+l9Ijwy1WpWdMJhMLFiwQzhvEdR/VW1V1HbhMyTbXOaK6i+oN4rqL6g3+uXZOOKsIwGazcezYMWbNmuVLJ10hs4okPqH5LPxiIRgt8HAFBIUG2kgikUj8jq6yiqYboo3mVhSF3bt3C+cN4rqP6l3WN75l5jW6DFqmZJvrHFHdRfUGcd1F9Qb/XDsvKXBZuXIlVqvVVy66RrTR3KqqYrfbhfMGcd1H9dbxbSKYom2uc0R1F9UbxHUX1RsCnFU0HPn5+b7ykEimLjof3yKRSCQiMe7ApampybNGUWVlJb/73e/o7u7mlltuYeXKlT4XlEiEp+EMdNaD2QozFwfaRiKRSITG61tFJ06cICMjg4SEBHJycjh69CjXXHMNP/vZz3jmmWdYs2YNr776qh9VA4too7lNJhO5ubnCeYO47iN698/fkrYUzMGTL+YFU67NBUBUd1G9QVx3Ub3BP9dOrwOXb3zjG1x55ZXs27eP1atXc/PNN7Nx40ba2tpoaWnh85//PD/60Y98LqgXRFvcymg0kpCQIJw3iOs+onfZW9pPHd8mmnJtLgCiuovqDeK6i+oN/rl2er3HQ4cO8YMf/IBrr72WJ598kvPnz/Pf//3fGI1GjEYjDzzwAKdPn/a5oF5wOp2BVhgXTqeTN954QzhvENd9WG+3+0JGUeaqwIh5wZRqc0EQ1V1UbxDXXVRv8M+10+vApbm5maSkJADCw8MJCwsjOjra83p0dDR2u93ngpKJI2LqXD+iug/xrjsBjlYIskHygkAoec2UaXOBENVdVG8Q111Ub38wrj4cg8Ew6u8SieQi+rOJ0peD6ZKS+CQSiUTCOLOK7rrrLoKDtcGFDoeD+++/n7CwMAB6enp8byeRiI7nNpF+x7dIJBKJSHg95f/dd9/t1Q6fe+65SxLSG/3TFbe2thIZKc6Kvv0TFtlsNuF6xkR1H+LtcsITGdDbAZ9/G5LnB1pxRKZMmwuEqO6ieoO47qJ6A7S1tREVFeXTKf+97nGZagHJdEDkWY1FdR/kff6oFrRYoyFxXsCcvGVKtLlgiOouqjeI6y6qtz8QL7cqQIg2MEpRFPLz84XzBnHdh3j3p0FnrACdpzFOmTYXCFHdRfUGcd1F9QYdrlUkkUhGoVz/adASiUQiGjJwkUj8gdIDFe9pz+XAXIlEIvEZMnCRSPxB1SFQHBCeCHGXBdpGIpFIpgxeZxVNV0TOKlIUBbPZLNwodFHdB3nv3QJvPQHzbofbfx9otTGZEm0ukDeI6y6qN4jrLqo3+CerSPa4TGG6u7sDrTBhRHX3eAs4f4vwbS4gorqL6g3iuovq7Q9k4OIloo3mVhSFPXv2COcN4rp7vLvatFtFIEzgInybC+YN4rqL6g3iuovqDTKrSCIRAkPVQXA7ITINojMCrSORSCRTChm4SCQ+xuBJg14Jgt2PlkgkEr0jA5cpjNks7qJ+orqbzWYM597RfhHkNlE/Ire5qIjqLqo3iOsuqrc/kFlFY9CfVeTLEdGSKYyjTVufSHXDVz+EyBmBNpJIJJKA4Y9rqOxx8RK32x1ohXHhdrupr68XzhvEdXe73bQez9eCltjZQgUtIre5iN4grruo3iCuu6je4J9rpwxcvMTlcgVaYVy4XC4KCgqE8wZx3V0uF02HXtF+Eew2kchtLqI3iOsuqjeI6y6qN/jn2ikDF4nEh8R1FGpPMlYGVkQikUimKDJwkUh8RVcTkd0V2nMZuEgkEolfkIGLl4g2zbLBYMBmswnnDeK6G8u1bCI1YS6ExwfYZnyI2uaieoO47qJ6g7juonqDf66dMqtoDGRWkcRrXvgonN0L8++Ajz8TaBuJRCIJODKrKICINprb7XZz7tw54bxBUPfak6hl+wBwz/1YYF0mgJBtjrjeIK67qN4grruo3iCzigKKaKO5XS4XR48eFc4bBHRXVdj+LQyqm+qoJbiy1gfaaNwI1+Z9iOoN4rqL6g3iuovqDTKrSCLRJ0XboOwtVFMwp1LuCLSNRCKRTGmECVyam5vZtGkTERERREVFce+999LR0THqe1avXo3BYBj0uP/++yfJWDItUHph+6MAuJfeT3ewWINyJRKJRDSEWfxg06ZN1NTUsHPnTpxOJ3fffTf33XcfW7duHfV9n/vc5/je977n+T00NHRCxxdtNLfBYCA+Pl44bxDM/dD/QXMphMWjXvsg8cdOi+F9EUK1+QBE9QZx3UX1BnHdRfWGaZxVVFhYyNy5czl06BCLFy8GYNu2beTl5VFVVUVKSsqw71u9ejULFizgqaeemvCxZVaRZES6muEXC7T1iT7yC1j0mUAbSSQSia7wxzVUiB6XgoICoqKiPEELwPXXX4/RaOTAgQPceuutI773xRdf5E9/+hNJSUl85CMf4Tvf+c6ovS49PT309PR4fm9vbwfA4XBgtVoBMBqNmEwmXC7XoBHT/eWKojAwHjSZTBiNxhHLnU7nIIf+VUAVRfGq3GKx4Ha7Bw2CcrvdlJWVkZWVNWhbg8GA2Wwe0V0PdXK5XJSXl4/ofnFdA1anvVswONpQE+ahzLsDl8NBaWkp2dnZnv0PZLjPSS91crlco7qP57s3mXVSFIXS0lKysrIICgry29+TP+o0nPtkniMmWqfe3l6Ki4vJysry+OnlvDdWnUZy18N5b7Q6GQwGioqKyMzMxGQyDaqTns/l4J/BuUIELrW1tSQkJAwqM5vNxMTEUFtbO+L7PvWpT5Genk5KSgrHjx/nm9/8JmfOnOHll18e8T1btmxh8+bNQ8p37drlCXjS0tJYuHAhx48fp6KiwrNNdnY2OTk5HDx4kIaGBk/5ggULSE9PZ9++fdjtdk95bm4uCQkJ7NixY9CHvWbNGqxWK/n5+YMc8vLy6O7uZs+ePYPaYePGjTQ2NlJQUOApDw8Pp6Ojg6CgIE6cOOEpj4+PZ/ny5RQXF3PmzBlPud7qpCgKERERHDp0yFNus9lYu3YtlZWVHD16NKB1CndUs/b07wHYH3Ezjdu2e7bPzMxEURSvPic91QkgOTkZm812Sd+9QNSppKTEr39P/qxTSUlJQM4RE63TiRMnqKqqoqSkZNyfkx7qVFJS4nHX23lvpDqtXLmSoqIiioqKvP6c9FKnZcuW4WsCeqvo4Ycf5oknnhh1m8LCQl5++WWef/75QR8OQEJCAps3b+YLX/iCV8fbvXs369ato6SkZMh/8/0M1+OSmppKTU0NsbGxgP4i2uGidEVR2LFjBzfeeCNG44Ux2CJE6U6nk507d47oHujeCQDTX/4DY+mbqNk3odz+x0HeN910ExaLRXe9E6PVaSz3QPdOjFSn3t5edu7cyfr16wkJCdFd78RodRrOXU+9EyO5OxwOtm/fzvr167FYLLo6741Vp5Hc9XDeG61OqqqSn5/v8R5YJz2fy0G7hsbFxU2dW0UPPfQQd91116jbzJo1i6SkJOrr6weVK4pCc3MzSUlJXh9v6dKlAKMGLsHBwQQHBw8pt1gsni9MPyaTydNtN5D+D9Db8ov3O5Fyo9E46CI/sHy47Udy11udxlPXSatTyS4ofROMFgwbfjDEsb9rd7yfU0Dr5IX7cNuP5j4Zdeo/0fZfhEZyHG/5ZNRpOPdAnSPGW6f+Yww8jt7OeyPVqX9fA/ent/Pexe79wcN4rkN6qpOvCWjgEh8fT3z82Omjubm5tLa28v7777No0SJA6z1xu92eYMQb+rsOk5OTx+063B+BnjEajaSlpQnnDTp3dyme9GeW3AexFwJgXXuPgajuonqDuO6ieoO47qJ6g3+unUJkFQHcdNNN1NXV8fTTT3vSoRcvXuxJh66urmbdunW88MILLFmyhNLSUrZu3UpeXh6xsbEcP36cr371q8ycOZO33nrL6+PKrCLJIA79Ht74Glhj4MtHwBodaCOJRCLRLdN6raIXX3yRnJwc1q1bR15eHitWrOCZZy4sZOd0Ojlz5gxdXV0ABAUF8eabb7JhwwZycnJ46KGHuO222/jXv/41oeOLNtWyy+Xigw8+EM4bdOze3Qp7fqA9X/3IkKBFt95eIKq7qN4grruo3iCuu6jeMM2n/I+JiWHr1q3Y7Xba2tp49tlnCQ8P97yekZGBqqqsXr0agNTUVN566y2amppwOBwUFxfz4x//eMIRn2iLW7ndbioqKoTzBh27v/0kdDVB3GWw+O4hL+vW2wtEdRfVG8R1F9UbxHUX1RvkIosSSeBoPgvvPa09v+GHYPL/ADSJRCKRDEUGLhKJN+z8LridkLUO5oi3+rNEIpFMFWTg4iWijeY2Go1kZ2cL5w06dC97Gwr/BQYT3PCDETfTnfc4ENVdVG8Q111UbxDXXVRvmOZZRYFCZhVNc9wueGY11B6HxffCzf8TaCOJRCIRhmmdVRRoLp4NUO8oisL+/fuF8waduR/7sxa0BEfCmm+NuqmuvMeJqO6ieoO47qJ6g7juonqDf66dMnDxEtE6plRVpaGhQThv0JF7Twfs+p72fNXXISxu1M114z0BRHUX1RvEdRfVG8R1F9Ub/HPtlIGLRDIS7z4FHXUQnanNkiuRSCSSgCMDF4lkOForYf8vtecbvg/moetXSSQSiWTykYGLlwy3WJWeMZlMLFiwQDhv0In7m4+D4oD0FZBzs1dv0YX3BBHVXVRvENddVG8Q111Ub/DPtVNmFY2BzCqahlQegt9fDxjg829B8lWBNpJIJBIhkVlFAUS00dyKorB7927hvCHA7qoK2x7Wni/cNK6gRbb55COqN4jrLqo3iOsuqjfIrKKAIlrHlKqq2O124bwhwO4n/g7Vh8ESBmu/M663yjaffET1BnHdRfUGcd1F9QaZVSSR+JfeLm1sC8DKr4ItKaA6EolEIhmKDFwkkn4Kfg3tVRCZCrlfCrSNRCKRSIZBDs4dg/6BRS0tLURFRQVax2vcbjeNjY3ExcUJt75FQNzba+CXi8DZCbf9Hq68fdy7kG0++YjqDeK6i+oN4rqL6g3Q2tpKdHS0TwfnysBlDGRW0TTh1f+Goy/CzCVw7w4wGAJtJJFIJMIjs4oCiNPpDLTCuHA6nbzxxhvCeUMA3M8fhaNbtec3bplw0CLbfPIR1RvEdRfVG8R1F9Ub/HPtlIHLFEbE1Ll+Js1dVWH7twAVrvwEzFx8SbuTbT75iOoN4rqL6g3iuovq7Q9k4CKZ3hT+C869C2YrXP94oG0kEolEMgYycJFMX5Qe2Nk3V8vyByByZmB9JBKJRDImcnDuGPQPLGptbSUyMjLQOl7TP2GRzWbDINhA00lzf/fnsPO7EJ4ED7wPweGXtDvZ5pOPqN4grruo3iCuu6jeAG1tbURFRcnBuRLvsFqtgVaYMH5372iAfU9qz9d995KDln5km08+onqDuO6ieoO47qJ6+wMZuHiJaAOjFEUhPz9fOG+YJPe9P4Sedm0toqvu9MkuZZtPPqJ6g7juonqDuO6ieoNcq0gi8Q11H8L7f9Ce37AFBJvQSSKRSKYz8owtmV70pz+rbrj8Fsi4NtBGEolEIhkHMnCRTC+Kd8DZPWAKgvXfC7SNRCKRSMaJzCoaA5GzihRFwWw2CzcK3W/uLif8JheaimH5l2HD9323b2SbBwJRvUFcd1G9QVx3Ub1BZhVJxkl3d3egFSaMX9wPP6sFLaFxcN3/8/3+kW0eCET1BnHdRfUGcd1F9fYHMnDxEtFGcyuKwp49e4TzBj+5dzXD3i3a87WPQojve89km08+onqDuO6ieoO47qJ6g8wqkkgmzls/hu4WSJgLC/8r0DYSiUQimSAycJFMfRqL4dDvtOc3/ABM5sD6SCQSiWTCyMBlCmM2i3uB9qn7ju+AW4E5N0DWWt/tdxhkm08+onqDuO6ieoO47qJ6+wOZVTQG/VlFvhwRLZlESvfAHz8GRjN8oQDiLwu0kUQikUwb/HENlT0uXuJ2uwOtMC7cbjf19fXCeYMP3d0u2P6o9vyaz/o9aJFtPvmI6g3iuovqDeK6i+oN/rl2ysDFS1wuV6AVxoXL5aKgoEA4b/Ch+5EXoP4UhETBqm/6xG00ZJtPPqJ6g7juonqDuO6ieoN/rp0ycJFMTRztsOcH2vPVD0NoTGB9JBKJROITZOAimZq8/VPobIDY2dptIolEIpFMCWTg4iWiTbNsMBiw2WzCeYMP3JvL4L3faM83/ABMFt/JjcK0bvMAIao3iOsuqjeI6y6qN/jn2imzisZAZhUJyF//Cz78J8xaDf/5Kgj4xy6RSCRTAZlVFEBEG83tdrs5d+6ccN5wie7n9mtBi8EIN/xwUoOWadvmAURUbxDXXVRvENddVG+QWUUBRbTR3C6Xi6NHjwrnDZfg7nbDtke051f/FyRe4Xu5UZiWbR5gRPUGcd1F9QZx3UX1BplVJJGMzvGXoOYoBNlgzbcDbSORSCQSPyBM4NLc3MymTZuIiIggKiqKe++9l46OjjHfV1BQwNq1awkLCyMiIoLrrrtOLg8+FenthF2btefX/T8Ijw+sj0QikUj8gjCBy6ZNmzh16hQ7d+7k9ddfZ9++fdx3332jvqegoIAbb7yRDRs2cPDgQQ4dOsSXvvQljMbxV1u00dwGg4H4+HjhvGGC7u/+HOw1EJUOy77gP7lRmHZtrgNE9QZx3UX1BnHdRfWGaZxVVFhYyNy5czl06BCLFy8GYNu2beTl5VFVVUVKSsqw71u2bBnr16/n+9///oSPLbOKBKCtGn65CJRu+MTzcMXHAm0kkUgkEvxzDRViucmCggKioqI8QQvA9ddfj9Fo5MCBA9x6661D3lNfX8+BAwfYtGkTy5cvp7S0lJycHH7wgx+wYsWKEY/V09NDT0+P5/f29nYAHA4HVqsVAKPRiMlkwuVyDRox3V+uKAoD40GTyYTRaByx3Ol0DnLoXwVUURSvyi0WC263e9AgKLfbTVlZGVlZWYO2NRgMmM3mEd31UCeXy0V5efmI7hfX1bTzMYxKN2paLsqcPOg79mTXyeVyUVpaSnZ2tmf/AxnucxqpTpP9OY3lPp7v3mTWSVEUSktLycrKIigoyG9/T/6o03Duk3mOmGident7KS4uJisry+Onl/PeWHUayV0P573R6mQwGCgqKiIzMxOTyTSoTno+l4N/BucKEbjU1taSkJAwqMxsNhMTE0Ntbe2w7zl79iwAjz/+OE8++SQLFizghRdeYN26dZw8eZI5c+YM+74tW7awefPmIeW7du0iNDQUgLS0NBYuXMjx48epqKjwbJOdnU1OTg4HDx6koaHBU75gwQLS09PZt28fdrvdU56bm0tCQgI7duwY9GGvWbMGq9VKfn7+IIe8vDy6u7vZs2fPoHbYuHEjjY2NFBQUeMrDw8Pp6OggKCiIEydOeMrj4+NZvnw5xcXFnDlzxlOutzopikJERASHDh3ylNtsNtauXUtlZSVHjx4FIKqzlFVFfwMMlOd8nuP//nfA65SZmYmiKF59TsPVCQL3OSUnJ2Oz2S7puxeIOpWUlPj178mfdSopKQnIOWKidTpx4gRVVVWUlJSM+3PSQ51KSko87no7741Up5UrV1JUVERRUZHXn5Ne6rRs2TJ8TUBvFT388MM88cQTo25TWFjIyy+/zPPPPz/owwFISEhg8+bNfOELQ8c07N+/n2uvvZZHHnmEH/7wh57y+fPns3HjRrZs2TLs8YbrcUlNTaWmpobY2FhAfxHtcFG6oijs2LGDG2+8cdCYHhGidKfTyc6dO0d099RVVTG9sBFj1UG46lO4bvlVQOvU733TTTdhsVh01zsxWp3Gcg9078RIdert7WXnzp2sX7+ekJAQ3fVOjFan4dz11DsxkrvD4WD79u2sX78ei8Wiq/PeWHUayV0P573R6qSqKvn5+R7vgXXS87kctGtoXFzc1LlV9NBDD3HXXXeNus2sWbNISkqivr5+ULmiKDQ3N5OUlDTs+5KTkwGYO3fuoPLLL798UBR6McHBwQQHBw8pt1gsni9MPyaTydNtN5D+D9Db8ov3O5Fyo9E47KBjo9E47PYjueutTqPW9eQ/oOogWEJh3Xd1U6f+rt3xfk7DlU92nUZzH2770dwno079J9r+i9BIjuMtn4w6DeceqHPEeOvUf4yBx9HbeW+kOvXva+D+9Hbeu9i9P3gYz3VIT3XyNQENXOLj44mPHzttNTc3l9bWVt5//30WLVoEwO7du3G73SxdunTY92RkZJCSkjKkl6aoqIibbrpp3K4TyUQKJEajkbS0NOG8wUt3ZzfsfFx7fu2DEJE8GWqjMuXbXIeI6g3iuovqDeK6i+oN/rl2CpFVBHDTTTdRV1fH008/jdPp5O6772bx4sVs3boVgOrqatatW8cLL7zAkiVLAHjqqad47LHH+P3vf8+CBQt4/vnnefLJJzl58uSQgZ8jIbOKdMq+J2H39yFiBnzpMASFBtpIIpFIJBcxrdcqevHFF8nJyWHdunXk5eWxYsUKnnnmGc/rTqeTM2fO0NXV5Sl78MEHeeSRR/jqV7/KVVddxa5du9i5c6fXQctARJtq2eVy8cEHHwjnDV642+vgnZ9pz69/XDdBy5Ruc50iqjeI6y6qN4jrLqo3TPMp/2NiYti6dSt2u522tjaeffZZwsPDPa9nZGSgqiqrV68e9L6HH36YyspKOjs72b9//6ip0KMh2uJWbrebiooK4bzBC/fd34feDpixCObdPrlyozCl21yniOoN4rqL6g3iuovqDXKRRYkEao7DB3/Snt+wBQS85yuRSCSSiSPP+hJxUFXY/i1AhSs+DmnDD8yWSCQSydRFBi5eItpobqPRSHZ2tnDeMIr76Teg/G0wBcP6oZMEBpop2eY6R1RvENddVG8Q111Ub5jmWUWBQmYV6QSlF36zFJrPwsqHYN13A20kkUgkkjGY1llFgebi2QD1jqIo7N+/XzhvGMH94DNa0BKeCCu+Gji5UZhybS4AonqDuO6ieoO47qJ6g3+unTJw8RLROqZUVaWhoUE4bxjGvbMJ3vqx9nzttyHYFji5UZhSbS4IonqDuO6ieoO47qJ6g3+unTJwkeifvT+EnjZIuhIWbAq0jUQikUgCiAxcJPqm/jQcfk57fsMWMA5de0MikUgk0wcZuHjJcItV6RmTycSCBQuE84aL3Hc8CqoLcm6GzJWBVhuVKdPmAiGqN4jrLqo3iOsuqjf459ops4rGQGYVBZDiN+HF28BogS8egNjxL9UgkUgkksAhs4oCiGijuRVFYffu3cJ5g+a+Z9dO1O2PaAVLPy9E0CJ6m4voLqo3iOsuqjeI6y6qN8isooAiWseUqqrY7XbhvEFzjy17DUNjEVhj4LqvB1rJK0RvcxHdRfUGcd1F9QZx3UX1BplVJJkudLeSXfOy9nzNt8AaFVAdiUQikegHc6AFJJKLMe77MRZXB2pcNoZFdwdaRyKRSCQ6Qva4eIloo7lNJhO5ubnCeXPsJYzv/x8A6ob/D0zixNbCtjniuovqDeK6i+oN4rqL6g0yqyggyKyiSUJV4d2n4M3Htd+z1sF/vhxII4lEIpFcIjKrKIA4nc5AK4wLp9PJG2+8IYa3S4E3HvIELa4l9/NG9N1iuA9AqDa/CFHdRfUGcd1F9QZx3UX1Bv9cO2XgMoURInWutxNe+jQc/j1ggBt/hHv9/4ficgfabEII0eYjIKq7qN4grruo3iCuu6je/kCcAQSSqUdHPWy9A84fAXMIfPwZmPtREPC/ColEIpFMDjJwkQSGxmL4023Qek6bq+XOv0Da0kBbSSQSiUTnyMG5Y9A/sKi1tZXIyMhA63hN/4RFNpsNg8EQaJ3BnCuAv9zJ/9/emcY3VewN+En3vaWlpS0WWlpZqigIgkXZQaCIKBcFRSiyuYsKKIu+bAqKeNWLKCK7gohQUKACFeGygyIoSy20wgW0rWzd6JZl3g+9zSV0S9qkycg8v18+ZDJnzjMnJ2f+mTNzhsKrUC8Knlhn8mRch3avAlm9QV53Wb1BXndZvUFed1m9AXJycggICLDq4FzV4/I3xtPT094K5TmxHhKfAn0xNGxb2tPiE1wum0O6m4Gs3iCvu6zeIK+7rN4gr7us3rZADc41E9kGRul0OpKSkhzHWwjY9xF8Pbw0aGnWFxI2Vhi0OJy7mcjqDfK6y+oN8rrL6g3yusvqDbZpO1WPi8L2GPSwdTIcXFD6/u7R0OcdcJLvYUoKhUKhsC8qcFHYlpICSBwNv20qfX//mxD3PEh2n1ahUCgUjoEKXBS249ol+HIwXPgRnN3g4U/h9gH2tlIoFAqFxKhZRdUg86winU6Hi4uLfUahX04vne589Qx4BMBjX0LjDmZtanf3GiKrN8jrLqs3yOsuqzfI6y6rN9hmVpEanPs3prCw0D47Pv8jLO5ZGrQENIKRyWYHLWXYzb2WyOoN8rrL6g3yusvqDfK6y+ptC1TgYiayjebW6XTs2LGj7r1TNsLyB6DgMoS1gpHfQ3BTi4qwm3stkdUb5HWX1RvkdZfVG+R1l9Ub1KwihaNz8FP47jVAwK29YOAScPext5VCoVAo/kaowEVRewwGSH4D9n9U+r7NkxA/F5zV6aVQKBQK66Jalr8xLi518PVqi2D9GDj5Ten77lPhvpdrPd25TtxtgKzeIK+7rN4gr7us3iCvu6zetkDNKqqGsllF1hwR/beh4Ap8+RicPwBOrvDQJ3DHI/a2UigUCoWDYIs2VA3ONRODwWBvBYswGAz89ddftvO+cgYW318atLj7w9D1VgtabO5uI2T1BnndZfUGed1l9QZ53WX1Btu0nSpwMRO9Xm9vBYvQ6/Xs37/fNt5/HC6d7nz5NPjdAiO3QlRHqxVvU3cbIqs3yOsuqzfI6y6rN8jrLqs32KbtVDfNFJaR+h2sHQHaAghtCY9/DX5h9rZSKBQKxU2CClwU5vPjIkiaAMIA0d3h0eXg7mtvK4VCoVDcRKjAxUxke8yyRqPB19fXOt4GA2yfDns/KH3feig88D44u9a+7AqwqnsdIqs3yOsuqzfI6y6rN8jrLqs32KbtVLOKquGmn1WkK4YNz8LxtaXvu74Oncar1Z0VCoVCUS1qVpEdkW00t8Fg4D//+U/tvAuvwucDSoMWJxd4aAF0nmDzoMUq7nZAVm+Q111Wb5DXXVZvkNddVm9Qs4rsimyjufV6PUePHq25d/Y5WNwL/rMH3HxhyFpo9Zh1JSuh1u52QlZvkNddVm+Q111Wb5DXXVZvULOKFHXFn0dh1aOQnwW+4TDkawi93d5WCoVCoVDI0+Ny5coVhgwZgp+fHwEBAYwcOZL8/PxK8589exaNRlPh6+uvv65Dc8k4nQxL40uDlpDbYNT3KmhRKBQKhcMgTeAyZMgQTpw4QXJyMps2bWLXrl2MGTOm0vwRERFkZGSYvKZPn46Pjw99+vSxeP+yjebWaDQEBwdb5n14OawaBNpr0KQLjPgO/BvazLEyauTuAMjqDfK6y+oN8rrL6g3yusvqDTfxrKKUlBRiY2P58ccfadu2LQBbtmwhPj6eCxcuEB4eblY5rVu35q677mLx4sVm7/ummFUkBOx4C3a9W/r+zseg37/Axc2+XgqFQqGQGlu0oVKMcdm/fz8BAQHGoAWgR48eODk5cfDgQR5++OFqyzh8+DBHjx5l/vz5VeYrLi6muLjY+D43NxeAoqIiPD09AXBycsLZ2Rm9Xm8yYrosXafTcX086OzsjJOTU6XpWq3WxKFsFVCdTmdWuqurKwaDwWQQlMFg4MyZM0RHR5vk1Wg0uLi4/M9dX4Lz5pdwOramdLuOE9B3fBWEBrRau9RJr9dz9uzZSt1vrGu5Ov2Xuv6e9Ho96enpNGvWzFj+9VT0PTlKnapzt+Tcq8s66XQ60tPTiY6Oxs3NzWa/J1vUqSL3urxG1LROJSUlnD59mujoaKOfo1z3qqtTZe6OfC0vG+Jw6tQpoqKicHZ2NqmTva971aXftINzMzMzCQkJMUlzcXEhMDCQzMxMs8pYvHgxLVq0oEOHDlXmmz17NtOnTy+Xvn37dry8vABo1KgRrVu35tdff+XcuXPGPM2aNaN58+YcOnSIixcvGtNbtWpF48aN2bVrF3l5ecb0uLg4QkJC2LZtm8mX3bVrVzw9PUlKSjJxiI+Pp7CwkB07dpgch759+3Lp0iX2799vTPfx8SE/Px83NzeOHTtmTA8ODqZDhw6cPn2a9JNHaPf7vwjOP4nQOKHp9yG/aFpy7rvv7F4nnU6Hn58fP/74ozHd19eXbt26cf78eY4ePVphnVJTU43p9vqeoqKi0Ol0Zn1PjlansLAwfH19a3Xu2aNOaWlpNv092bJOaWlpdrlG1LROx44d48KFC6SlpVn8PTlCndLS0ozuMlzLfX196dixI6dOneLUqVNmf0+OUqd77rkHa2PXW0UTJ07knXfeqTJPSkoKiYmJLF++3OTLAQgJCWH69Ok888wzVZZRWFhIWFgYb7zxBuPGjasyb0U9LmXjZYKCggDHi2gritJ1Oh3btm2jd+/eODn9byiTMUq/8h+cvhyE5mIKws0bw8BlODe93yHqpNVqSU5OrtTd3r0TlbmXeffp0wdXV1eH652oqk7Vudu7d6KyOpWUlJCcnEzPnj3x8PBwuN6JqupUkbsj9U5U5l5UVMTWrVvp2bMnrq6uDnXdq65Olbk7wnWvqjoJIUhKSjJ6X18ne1/3qkvPzc2lfv36f59bRePGjWP48OFV5mnSpAmhoaH89ddfJuk6nY4rV64QGhpa7X7Wrl1LQUEBw4YNqzavu7s77u7u5dJdXV2NJ0wZzs7Oxm676yn7As1Nv7HcmqQ7OTmZNPLXp5fLn3kM55WPQF4G+ISiGbIG57A7AcerkyV1rcy9rutU1rVr6ffkCHWqyr2i/FW510Wdyi60ZY1QZY6WptdFnSpyt9c1wtI6le3j+v042nWvsjqVlXV9eY523bvRvSx4sKQdcqQ6WRu7Bi7BwcEEBwdXmy8uLo7s7GwOHz5MmzZtAPjhhx8wGAy0b9++2u0XL17Mgw8+aNa+KqOiH4Ej4+TkRKNGjcp7p/8AXw2DkjwIbl76YLmACPtIVkKl7g6OrN4gr7us3iCvu6zeIK+7rN5gm7ZTillFAH369CErK4sFCxag1Wp58sknadu2LatWrQLgjz/+oHv37qxYsYJ27doZt0tLS6Np06YkJSXRu3dvi/f7t5pVdGQlbHwRDDqI7AiDPgfPeva2UigUCsXflJt6raKVK1fSvHlzunfvTnx8PPfddx8LFy40fq7VaklNTaWgoMBkuyVLlnDLLbdw//3312r/sj1qWa/Xc+TIkVJvIWDn2/DNs6VBS8tH4Il1Dhu0mLhLhKzeIK+7rN4gr7us3iCvu6zeYJu2U5rAJTAwkFWrVpGXl0dOTg5LlizBx8fH+HlkZCRCCLp06WKy3axZszh37lytu6tkW9zKYDBw7tw5DNpi+OZ52Dm79IP7XoGHF4JL+XE8joLRXdZjLpk3yOsuqzfI6y6rN8jrLqs32KbtlGI6tKJmuOgLcV7zOPy+AzRO0Pc9aDvC3loKhUKhUNQYFbj8XblyhvtOv4VT4Tlw9YJHlkHTXva2UlgBvV5fbopibdFqtcbpojJ1R8vqDbZ1d3V1rXBGiULxd0AFLmYizWhuIeCXL3HZPB5/7TWEZyCaJ9ZBw7vsbWY2Tk5ONGvWTJ5j/l9s7S2EIDMzk+zsbJuUHRERwfnz56VaD0VWb7C9e0BAAKGhoVYvW9bfJ8jrLqs33OSziuyFVLOKcjNg41g4vbX0ff2mMGglBDe1r5fCKmRkZJCdnU1ISAheXl7SNdSKukEIQUFBAX/99RcBAQGEhYXZW0lxE3PTrlXkCNz4NECHQgj4ZTVseQ2KcsDZDX3niRx0ake7ek2k+5J1Oh2HDh2iXbt2lT4UyRGxpbderzcGLWVPcLYmQgiuXbuGt7e3VAGRrN5gW/eyddX++usvQkJCrHrbSNbfJ8jrLqs32KbtlOsI2BGH7ZjKy4SNL8Gp/64vFN4aHvoEQ70YLiYlOa53FQghuHjxonTutvQuG9NStl6WtRFCGB/5LVMAIKs32N697FzRarVWDVxk/X2CvO6yeoNt2k4VuMiKEPDrGvjuVSjKBmc36DIROowFZxew8uBNhWMgW+OssB/qXFH8XVGBi4zkZcGmlyD1v6tzhrWChz6BBrH2tFIoFAqFwubIN0TZTjjE1EIh4Nev4eP2pUGLkyt0ex1GfV8uaHF2dqZVq1aO4W0hsrrL6g2l/849PT2l+5deW+9p06bRqlUr60qZiazHXObzXFZ3Wb3BNm2nClzMxO7T0PL/gq+egMRRUHgVwu6Ep/4NnSaAc8UrjDZu3Nj+3jVAVndZvaG0EXV3d7dJIzp8+HDjqtPXv9LS0gD45ZdfePDBBwkJCcHDw4PIyEgGDRpkXBH+7NmzJtsFBgbSuXNndu/ebeJdUFDApEmTiI6OxsPDg+DgYDp37sw333xj9TpVhzl1cnJywsvLiz///NNk24yMDFxcXNBoNJw9e9ZY3mOPPUZERASenp60aNGCDz/8sK6rBch9nsvqLqs32KbtlO8o2Am7zSoSAo6thfnt4LdNpb0sXafAqO3Q4LZKN9PpdPzwww+OPRuqEmR1l9UbSgfQ5ebm2mzwX+/evcnIyDB5RUVFcfHiRbp3705gYCBbt24lJSWFpUuXEh4ezrVr10zK+P7778nIyGDXrl2Eh4fzwAMPkJmZafR++umnSUxMZN68efz2229s2bKFgQMHcvnyZZvUqTIsqVN4eDjLly83SVu+fDkNGzY0STt8+DAhISF88cUXnDhxgilTpjBp0iQ++ugjm9fnRmQ+z2V1l9Ub1Kwiu2KX0dz5F2Hzy5CysfR9aEt4aAGE3l7tpkII8vLypB2FLqN7XXsLISjUWueJqwaDgWtFWpzctGb9Q/J0dbaod8bd3Z3Q0NBy6Xv37iUnJ4dFixYZp3lGRUXRtWvXcnmDgoIIDQ0lNDSUyZMns3r1ag4cOECXLl0QQvDtt9/y4YcfEh8fD5SuX9amTRuz/D799FPefPNNLl++zAMPPMBnn32Gv78/u3btonv37pw/f97E/6WXXuLw4cPs3r27VnUaPHgwy5YtY/Lkyca0pUuXkpCQwMyZM41pI0aYLtXRpEkT9u/fT2JiIs8//7xZdbQWsv4+QV53Wb1BzSq6uTieCJvHQeEVcHKBTq9Cx1cqvC2kuDkp1OqJ/b+tdtn3yRm98HKr/eUjNDQUnU7H+vXrGThwoFnBUGFhIStWrADAzc3NpKykpCQGDBiAr6+v2Q5paWmsWbOGjRs3kpuby8iRI3n22WdZuXIlnTp1okmTJnz++edMmDABKJ1evHLlSubMmVPrOvXp04dly5axZ88e7rvvPvbs2cPVq1fp16+fSeBSETk5OQQGBppdT4Xi74K6VeRo5F+ENcNg7ZOlQUuDljB6B3R5TQUtCmnZtGkTPj4+xtcjjzwCwD333MPkyZN5/PHHqV+/Pn369OHdd98lKyurXBkdOnTAx8cHb29v5s6dS5s2bejevbvx84ULF7Jv3z6CgoK4++67efnll9m7d2+1bkVFRaxYsYJWrVrRqVMn5s2bx+rVq8nMzARg5MiRLF261Jh/48aNFBUV8eijj1ZYniV1cnV1ZciQISxZsgSAJUuW8MQTT+DqWvVvfd++fXz11VeMGTOm2vopFH87hKJKcnJyBCCuXr1q+50dTxTinSghpvoJMT1QiB9mCaEtrlFRer1eZGVlCb1eb2VJ2yOruy29CwsLxcmTJ0VhYaExzWAwiGvFWqu88otKRHZ+gcgvKjErv8FgMNs9ISFB9OjRQ5w+fdr4+vPPP03yXLp0SaxZs0aMGzdONGnSRAQEBIhff/1VCCHEmTNnBCC+/fZbcerUKZGYmChiYmLEsWPHhMFgECUlJUafkpISsWvXLvH222+Lnj17Co1GI2bMmFGp29SpU0VUVJRJWnZ2tgDEzp07hRBCZGVlCVdXV7F//34hhBD9+vUTI0aMqLbe5tTp0KFD4pdffhE+Pj4iIyND+Pj4iGPHjokjR44IQJw5c6ZcuceOHRP169cXM2fOrHL/FZ0z1kDW36cQ8rrL6i2EEFevXhWAyMnJsVqZKnCphrLAxZoHvRz5F4VYk1AasEz1E2J+nBB/HrXd/hTSYatGqC5ISEgQ/fv3Nzt/cXGxiI2NFcOGDRNC/K+RP3LkiDHPmjVrRExMjCgqKqqyrJkzZwpXV1dRXFzxHwBzAhchhBgwYIAYM2aMyMzMFC4uLmLPnj1m18ecOrVt21Z06dJF3H333UIIUWngcuLECRESEiImT55c7T5lPmcUfx9s0YaqW0VmorXVk2hPfgPz28OJ9aBxLh3LMmZn6XTnWqDVatm8ebPtvG2IrO6yekPp4Nzs7GwMBoO9VXBzcyM6OrrcDJzrGThwIC4uLsyfP79K79jYWHQ6HUVFRZWWde7cOZMpyQcOHDCuxlvGqFGj+Oqrr1i4cCHR0dHce++9VqlTXl4eBoOBESNGsHPnznKDcK/nxIkTdO3alYSEBN566y2L9m9NZD7PZXWX1Rts03aqwbn24tplSBoPJxJL34fEwkMfl641ZCVknDpXhqzusnrbi02bNrF69WoGDx5M06ZNEUKwceNGkpKSTMaV3IhGo+HFF19k2rRpDB48GD8/P7p06cJjjz1G27ZtCQoK4uTJk0yePJmuXbtWuSqth4cHCQkJzJ07l9zcXF588UUeffRRk1lEvXr1ws/PjzfffJMZM2ZYvU6jR4/mkUceISAgoMLPjx8/Trdu3ejVqxevvPKKcfyNs7MzwcHBVfrYApnPc1ndZfW2BarHxR6kbCx9+u2JxNJelo7jS3tZrBi0KBQyEBsbi5eXF+PGjaNVq1bcc889rFmzhkWLFjF06NAqt01ISECr1fLZZ58BpcHF8uXLuf/++2nRogUvvPACvXr1Ys2aNVWWExMTw4ABA4iPj+f+++/njjvu4OOPPzbJ4+TkxPDhw9Hr9QwbNszqdXJxcaF+/fqVrvy7du1aLl68yBdffEFYWJjxdffdd1fpolD8HVE9LnVJwRVImgDH15a+D25R2svS8C77eikUNmTZsmWVftakSRMWLlxY5faRkZEVPgvCy8uLS5cukZubC8CkSZOYNGmSRW7Tpk1j2rRpADzzzDNV5v3jjz+Ij48nLCysynzm1kmv1xvdb6RVq1Ymdb7eU6G42VGBi5lU9k/IbH7bDBtfgmt/gcYJ7n2pdDVnF3dr6JXDxcWFrl271t7bDsjqLqs3lN568fX1lW7dnLrwzsnJ4dixY6xatYpvv/3WauXKesxlPs9ldZfVG6zQdlZUptVLVJhScAW+ew2O/be7un6z0pWcbzHviZ61wdPT0+b7sBWyusvqDUjXgJZha+/+/ftz6NAhnn76aXr27GnVsmU95jKf57K6y+ptC9QYFzOp0cCo35Lg43tKg5ayXpandtVJ0KLT6UhKSpJyQJes7rJ6g+3XKrIVdeG9c+dOCgoKeP/9961arqzHXObzXFZ3Wb1BrVUkD4VX4buJ8Ovq0vf1m/63l6Wtfb0UCoVCoZAcFbhYm9QtsHEs5GeW9rLEPV+6mrOrh73NFAqFQqGQHhW4WIvCq7BlEvzyZen7oFtLe1ki1HRFhUKhUCishUbIdoO1jsnNzcXf35/s7Gz8/f0rznRqG2x8EfIyAA3EPQfdXgdX+w2mEkKg0+lwcXGRbgCgrO629C4qKuLMmTNERUXh4WH93jtRuvwHGo1GumMuozfY3t1W54ysv0+Q111WbyidlRcQEEBOTk6VD4K0BDU4tzYUZsOGZ2HVI6VBS1AMjNgKvd6ya9Bi1CsstLdCjZHVXVZvQLpBomXI6g3yust8nsvqLqu3LVCBi5mUGxl9Ohk+joOjKyntZXkent4Djdrbxe9GdDodO3bskHYUuozusnpDaQOal5cnXUMqqzfI6y7zeS6ru6zeYJtZRSpwsZSiHPjmOVg5EPL+hMAm8OR3DtPLolAoKiYyMpIPPvjA3hoKhaKWqMDFEtK+L+1lOfIFoIF7noWn90LjOHubKRQOy8WLF3nmmWdo1KgR7u7uhIaG0qtXL/bu3WvMExkZiUajYfXq1eW2v+2229BoNMalA65cucILL7xAs2bN8Pb25vbbb2fs2LHk5OTUVZWM7Ny50zhG5frX66+/DkBBQQGTJk0iOjoaDw8PgoOD6dy5M998842xjG7duhm38/DwoGnTpsyePbtcT8z69eu555578Pf3x9fXl9tuu42XXnqpLqurUDgEalaRmThvnQin/vv023pRpWsMNe5gX6lqkPHx0GXI6i6rty35xz/+QUlJCcuXL6dJkyZkZWWxfft2Ll++bJIvIiKCpUuXMnjwYGPagQMHyMzMxNvb25j2559/8ueffzJ37lyaN29OSkoK48ePJyMjg7Vr19ZZva4nNTXVZOChj48PAE8//TQHDx5k3rx5xMbGcvnyZfbt21eu7qNHj2bGjBkUFxfzww8/MGbMGAICAozrJ23fvp1Bgwbx1ltv8eCDD6LRaDh58iTJycl1V8nrkPk8l9VdVm+bIBRVkpOTIwCRM9FXiKl+QiS9KkRxvr21FDcZhYWF4uTJk6KwsPB/iQZD6bloj5fBYJb31atXBSB27txZZb7GjRuLiRMnCnd3d3Hu3Dlj+ujRo8ULL7wg/P39xdKlSyvdfs2aNcLNzU1otdoq9zFjxgwxePBg4eXlJcLDw8VHH31k/PzJJ58Uffv2NdmmpKREBAcHi0WLFlVY5o4dOwQgrl69WuHn/v7+YtmyZZU6CSFE586dxdixY03S7rrrLvHwww8b348dO1Z06dKlynJupMJzRqGoY4xtaE6O1cpUIZyZiIBGMGgBRN5nbxWzMBgMXLp0ifr16+PkJNcdQVnd69xbWwCzwm2/n4qY/Ce4eVebzcfHBx8fHzZs2MA999yDu3vli4o2aNCAXr16sXz5cl5//XUKCgr46quv+Pe//82KFSsq3Eb8d5podnY2fn5+1f4rfffdd5k8eTLTp09n69atjB07lqZNm9KzZ09GjRpFp06dyMjIMK4AvWnTJgoKChg0aFC1da2I0NBQkpKSGDBgAL6+vhW635i2Z88efvvtN2699VaTclatWsXx48e5/fbba+RiLWT9fYK87rJ6Q6m7tZHrCNgR3bAkaYIWAL1ez/79+9Hr9fZWsRhZ3WX1tiUuLi4sW7aM5cuXExAQwL333svkyZP59ddfK8w/YsQIli1bhhCCtWvXEh0dTatWrSotXwjBuXPnePPNNxkzZky1Pvfeey8TJ06kadOmvPDCCwwcONC4BlGHDh1o1qwZn3/+uTH/0qVLeeSRR4y3firjlltuMQZpPj4+xltBCxcuZN++fQQFBXH33Xfz8ssvG8f2CCG4du0aAB9//DE+Pj64u7vTqVMnDAYDL774orH8F154gbvvvpuWLVsSGRnJ4MGDWbJkCcXFxdXW2drIfJ7L6i6rN2ATZ9XjYi5m/LtUKOoUV6/Sng8rYDAYyM3Lw8/X17x/dK5eZpf9j3/8g759+7J7924OHDjAd999x5w5c1i0aBHDhw83ydu3b1+eeuopdu3axZIlSxgxYkSVZefm5jJo0CBatGjBtGnTqnWJi4sr9/76mUajRo1i4cKFvPrqq2RlZfHdd9/xww8/VFvu7t27TXpU6tWrB0CnTp34/fffOXDgAPv27WP79u18+OGHTJ8+nSlTphjzDxkyhClTpnD16lWmTp1Khw4d6NDhf2PovL292bx5M+np6ezYsYMDBw4wbtw4PvzwQ/bv34+Xl/nfh0IhO6rHRaGQFY2mNKC21svVy/y8Fj6908PDg549e/LGG2+wb98+hg8fztSpU8vlc3FxYejQoUydOpWDBw8yZMiQSsvMy8sjPj4eHx8fEhMTcXV1tfgQ3siwYcP4/fff2b9/P1988QVRUVF07Nix2u2ioqKIiYkxvq4P/lxdXenYsSOvvfYa27ZtY8aMGcycOZOSkhJjHn9/f2JiYrj77rtZs2YNH330Ed9//325/URHRzNq1CgWLVrEzz//zMmTJ/nqq69qXW+FQiZU4GImsj1mWaPR4OvrK503yOsuqzeUujs5OdWZe2xsrPE2yY2MGDGCf//73/Tv39/Yc3Ejubm53H///bi5ubF69Wo8Pc17htKBAwfKvW/RooXxfVBQEA899BBLly5l2bJlPPnkk2bWyHxiY2PR6XQUFxdX2Lvl4+PD2LFjGT9+fJUPp4uMjMTLy6vS42grZD/PZXSX1Rts03aqW0VmIttUNBcXF7p162ZvjRohq7us3lB6cbHWOiLXc/nyZR555BFGjBjBHXfcga+vLz/99BNz5syhf//+FW7TokULLl26VOntj7KgpaCggC+++AKArKwsAIKDg3F2dq7UZ+/evcyZM4eHHnqI5ORkvv76azZv3mySZ9SoUTzwwAPo9XoSEhJqUm0jXbp04bHHHqNt27YEBQVx8uRJJk+eTNeuXStf+wx46qmnmDlzJuvWrWPgwIFMmzaNgoIC4uPjady4MdnZ2fzrX/9Cq9XSs2fPWjlaisznuazusnqDbdpOuVpjO2KLkdG2xGAwcP78eSIiIqQchS6ju6zeUDpQtKSkBDc3N6v+Q/Lx8aF9+/a8//77pKeno9VqiYiIYPTo0UyePLnS7YKCgir97Oeff+bgwYMAxMTEmHx25swZIiMjK9123Lhx/PTTT0yfPh0/Pz/++c9/0qtXL5M8PXr0ICwsjNtuu43w8NrN2iqbJTV58mQKCgoIDw/ngQce4P/+7/+Mx7wiAgMDGTZsGNOmTWPAgAF07tyZ+fPnM2zYMLKysqhXrx6tW7dm27ZtNGvWrFaOliLzeS6ru6zeYJu2U60OXQ1lq0NfunSpyoupo6HVaklKSiI+Pt4q9/7rElndbelt69WhDQYDubm5+Pn5SXVhtIV3fn4+DRs2ZOnSpQwYMMAqZVaErY+5rc4ZWX+fIK+7rN5Q2utav359q64OrXpcFAqFgv89K+O9994jICCABx980N5KCoWiAqT5a3XlyhWGDBmCn58fAQEBjBw5kvz8/Cq3yczMZOjQoYSGhuLt7c1dd93FunXr6shYoVDIxLlz52jQoAGrVq1iyZIl0o1rUyhuFqT5ZQ4ZMoSMjAySk5PRarU8+eSTjBkzhlWrVlW6zbBhw8jOzubbb7+lfv36rFq1ikcffZSffvqJ1q1bW7R/2UZzazQagoODpfMGed1l9YZSdxcXF+ncrekdGRlZ5SweayPzMZf5PJfRXVZvsE3bKcUYl5SUFGJjY/nxxx9p27YtAFu2bCE+Pp4LFy5UOoDOx8eHTz75hKFDhxrTgoKCeOeddxg1apRZ+y4b42LN+3MKhaXYeoyL4u+HOmcUjoAt2lApelz2799PQECAMWiB0pH/Tk5OHDx4kIcffrjC7Tp06MBXX31F3759CQgIYM2aNRQVFdGlS5dK91VcXGzyGO3c3Fyg9CJQ9qwIJycnnJ2d0ev1JiOmy9J1Op3JPzdnZ2ecnJwqTddqtSYOZV3UN65jUlm6q6srBoPB5NHKBoOBM2fOEB0dbZK37F9eZe6OUCe9Xs/Zs2crdb+xro5SJ71eT3p6Os2aNTOWfz0VfU/m1qnMqaweQggTR41Gg0ajsTj9+uNSXFxsbOBu/D9T9q/pxnQnJyerudQ0vbi4GHd39wrrVJW7I9TpRndzvidz66TX603WQ6rpuXf9cXF2dqakpITTp08THR1t/G04ynWvujpV5u4I172q6qTRaDh16hRRUVHG6f6Oct2rLv2mfeR/ZmYmISEhJmkuLi4EBgaSmZlZ6XZr1qxh0KBBBAUF4eLigpeXF+vXry83hfJ6Zs+ezfTp08ulb9++3fhciUaNGtG6dWt+/fVXzp07Z8zTrFkzmjdvzqFDh7h48aIxvVWrVjRu3Jhdu3aRl5dnTI+LiyMkJIRt27aZfNldu3bF09OTpKQkE4f4+HgKCwvZsWOHyXHo27cvly5dYv/+/cZ0Hx8f8vPzcXNz49ixY8b04OBgOnTowOnTp0lNTTWmO1qddDodfn5+/Pjjj8Z0X19funXrxvnz5zl69KjD1ikqKgqdTmfW92RunTQaDWFhYWRnZ+Pl5UVhYaHJVFp3d3c8PT25du2aiaOnpyfu7u7k5eWZXMS8vb1xdXU1BuZluLq64uTkVC7dz88PIYTJcQEICAhAp9OZPATNyckJPz8/SkpKKCwsNDkGPj4+FBUVmfw5cHNzq3WdiouLK61T2YO7HLVOxcXFFn9P5tQpLy+Pa9eusWvXLuLj42t87pVR9ns6duwYFy5cIC0tDXCs6545dUpLSzO6O9p1r7I6dezYkVOnTnHq1CmzvydHqdM999yDtbHrraKJEyfyzjvvVJknJSWFxMREli9fbvLlAISEhDB9+nSeeeaZCrd94YUXOHToELNmzaJ+/fps2LCB999/n927d9OyZcsKt6moxyUiIoKMjAzjdGhHi2gritJ1Oh3btm2jd+/eJlMtZYjStVotycnJlbo7ao9LmXefPn1wdXW1ao8LlD5kLS8vj5CQkHJPiq1tj0vZgn8+Pj7G/DeWX5bveuzd42IwGLh27Rre3t7GJ//K0uNSkbs1elzKvsuLFy/i5+dHgwYNan3ulR0XZ2dnioqK2Lp1Kz179jQGuo5y3auuTpW5O8J1r6o6CSFISkoyel9fJ3tf96pLz83N/XtNhx43bly5RdZupEmTJoSGhvLXX3+ZpOt0Oq5cuUJoaGiF26Wnp/PRRx9x/PhxbrvtNgDuvPNOdu/ezfz581mwYEGF27m7u+Pu7l4u3dXVtdz8eWdn5wqf0lnZbITK0iubl29JupOTU4XPgnBycqowf2XujlYnS+rqKHUqa2ws/Z6qq1PDhg3JzMws91uwBkIICgsL8fT0lGoAoKzeYHv3evXqERoaaiy7NufejelQ/proaNe9yupUVtb15Tnade9G97LgwZJ2yJHqZG3sGrgEBwcTHBxcbb64uDiys7M5fPgwbdq0AeCHH37AYDDQvn37CrcpKCgAKHcCODs71+hJfjI9lAtKfRs1aiSdN8jrbmvvsttFISEh5f4F1Ra9Xk9qaiqNGzeu8pH5joas3mBbd1dXV5sdD1l/nyCvu6zeYJu2U4pZRQB9+vQhKyuLBQsWGKdDt23b1jgd+o8//qB79+6sWLGCdu3aodVqiY2NJSwsjLlz5xIUFMSGDRuYMGECmzZtIj4+3qz9qllFCoVCoVDUDFu0odKEbytXrqR58+Z0796d+Ph47rvvPhYuXGj8XKvVkpqaauxpcXV1JSkpieDgYPr168cdd9zBihUrWL58udlBy/XYYmS0LdHr9Rw5ckQ6b5DXXVZvkNddVm+Q111Wb5DXXVZvsE3bKU3gEhgYyKpVq8jLyyMnJ4clS5bg4+Nj/Lzs4VHXT3W+9dZbWbduHVlZWVy7do1ffvnF5JkuliDjIovnzp2TzhvkdZfVG+R1l9Ub5HWX1RvkdZfVG2zTdkoTuCgUCoVCoVBI8RwXe1I2BCgvL0+qVTm1Wi0FBQXk5uZK5Q3yusvqDfK6y+oN8rrL6g3yusvqDRifDWPN4bQqcKmGy5cvA6UPFVMoFAqFQmE5ly9fxt/f3yplqcClGgIDA4HSlWOtddDrgrIH550/f1662VCyusvqDfK6y+oN8rrL6g3yusvqDZCTk0OjRo2Mbak1UIFLNZTNQff395fuhIHSR4DL6A3yusvqDfK6y+oN8rrL6g3yusvqDdZ9nosanKtQKBQKhUIaVOCiUCgUCoVCGlTgUg3u7u5MnTq1wvWLHBlZvUFed1m9QV53Wb1BXndZvUFed1m9wTbu0jzyX6FQKBQKhUL1uCgUCoVCoZAGFbgoFAqFQqGQBhW4KBQKhUKhkAYVuCgUCoVCoZAGFbgA8+fPJzIyEg8PD9q3b8+hQ4eqzP/111/TvHlzPDw8aNmyJUlJSXVkaool3idOnOAf//gHkZGRaDQaPvjgg7oTrQBL3D/77DM6duxIvXr1qFevHj169Kj2O7IVlngnJibStm1bAgIC8Pb2plWrVnz++ed1aGuKped5GatXr0aj0fDQQw/ZVrASLPFetmwZGo3G5OXh4VGHtqZYesyzs7N57rnnCAsLw93dnaZNm9rl+mKJd5cuXcodc41GQ9++fevQ+H9Yesw/+OADmjVrhqenJxEREbz88ssUFRXVke3/sMRbq9UyY8YMoqOj8fDw4M4772TLli11aFvKrl276NevH+Hh4Wg0GjZs2FDtNjt37uSuu+7C3d2dmJgYli1bZvmOxU3O6tWrhZubm1iyZIk4ceKEGD16tAgICBBZWVkV5t+7d69wdnYWc+bMESdPnhSvv/66cHV1FceOHXNo70OHDonx48eLL7/8UoSGhor333+/Tn2vx1L3xx9/XMyfP18cOXJEpKSkiOHDhwt/f39x4cIFh/besWOHSExMFCdPnhRpaWnigw8+EM7OzmLLli116i2E5e5lnDlzRjRs2FB07NhR9O/fv25kr8NS76VLlwo/Pz+RkZFhfGVmZtaxdSmWuhcXF4u2bduK+Ph4sWfPHnHmzBmxc+dOcfToUYf2vnz5ssnxPn78uHB2dhZLly6tU28hLHdfuXKlcHd3FytXrhRnzpwRW7duFWFhYeLll192aO9XX31VhIeHi82bN4v09HTx8ccfCw8PD/Hzzz/XqXdSUpKYMmWKSExMFIBYv359lfl///134eXlJV555RVx8uRJMW/evBpdE2/6wKVdu3biueeeM77X6/UiPDxczJ49u8L8jz76qOjbt69JWvv27cVTTz1lU88bsdT7eho3bmzXwKU27kIIodPphK+vr1i+fLmtFCuktt5CCNG6dWvx+uuv20KvSmrirtPpRIcOHcSiRYtEQkKCXQIXS72XLl0q/P3968iuaix1/+STT0STJk1ESUlJXSlWSG3P8/fff1/4+vqK/Px8WylWiqXuzz33nOjWrZtJ2iuvvCLuvfdem3reiKXeYWFh4qOPPjJJGzBggBgyZIhNPavCnMDl1VdfFbfddptJ2qBBg0SvXr0s2tdNfauopKSEw4cP06NHD2Oak5MTPXr0YP/+/RVus3//fpP8AL169ao0vy2oibejYA33goICtFqtVRftqo7aegsh2L59O6mpqXTq1MmWquWoqfuMGTMICQlh5MiRdaFZjpp65+fn07hxYyIiIujfvz8nTpyoC10TauL+7bffEhcXx3PPPUeDBg24/fbbmTVrFnq9vq60rfL7XLx4MYMHD8bb29tWmhVSE/cOHTpw+PBh422Z33//naSkJOLj4+vEGWrmXVxcXO4WqKenJ3v27LGpa22xVvt5Uwculy5dQq/X06BBA5P0Bg0akJmZWeE2mZmZFuW3BTXxdhSs4f7aa68RHh5e7gdgS2rqnZOTg4+PD25ubvTt25d58+bRs2dPW+uaUBP3PXv2sHjxYj777LO6UKyQmng3a9aMJUuW8M033/DFF19gMBjo0KEDFy5cqAtlIzVx//3331m7di16vZ6kpCTeeOMN3nvvPd588826UAZq//s8dOgQx48fZ9SoUbZSrJSauD/++OPMmDGD++67D1dXV6Kjo+nSpQuTJ0+uC2WgZt69evXin//8J6dPn8ZgMJCcnExiYiIZGRl1oVxjKms/c3NzKSwsNLucmzpwUcjH22+/zerVq1m/fr1dB12ai6+vL0ePHuXHH3/krbfe4pVXXmHnzp321qqSvLw8hg4dymeffUb9+vXtrWMRcXFxDBs2jFatWtG5c2cSExMJDg7m008/tbdatRgMBkJCQli4cCFt2rRh0KBBTJkyhQULFthbzWwWL15My5Ytadeunb1VzGLnzp3MmjWLjz/+mJ9//pnExEQ2b97MzJkz7a1WJR9++CG33norzZs3x83Njeeff54nn3zSqiswOzIu9hawJ/Xr18fZ2ZmsrCyT9KysLEJDQyvcJjQ01KL8tqAm3o5Cbdznzp3L22+/zffff88dd9xhS81y1NTbycmJmJgYAFq1akVKSgqzZ8+mS5cuttQ1wVL39PR0zp49S79+/YxpBoMBABcXF1JTU4mOjratNNY5z11dXWndujVpaWm2UKyUmriHhYXh6uqKs7OzMa1FixZkZmZSUlKCm5ubTZ2hdsf82rVrrF69mhkzZthSsVJq4v7GG28wdOhQYw9Ry5YtuXbtGmPGjGHKlCl1EgjUxDs4OJgNGzZQVFTE5cuXCQ8PZ+LEiTRp0sTmvrWhsvbTz88PT09Ps8u5OcKzSnBzc6NNmzZs377dmGYwGNi+fTtxcXEVbhMXF2eSHyA5ObnS/LagJt6OQk3d58yZw8yZM9myZQtt27atC1UTrHXMDQYDxcXFtlCsFEvdmzdvzrFjxzh69Kjx9eCDD9K1a1eOHj1KRESEQ3pXhF6v59ixY4SFhdlKs0Jq4n7vvfeSlpZmDBIBTp06RVhYWJ0ELVC7Y/71119TXFzME088YWvNCqmJe0FBQbngpCxwFHW0jF9tjrmHhwcNGzZEp9Oxbt06+vfvb2vdWmG19tOyccN/P1avXi3c3d3FsmXLxMmTJ8WYMWNEQECAcQrl0KFDxcSJE4359+7dK1xcXMTcuXNFSkqKmDp1qt2mQ1viXVxcLI4cOSKOHDkiwsLCxPjx48WRI0fE6dOn69S7Ju5vv/22cHNzE2vXrjWZdpmXl+fQ3rNmzRLbtm0T6enp4uTJk2Lu3LnCxcVFfPbZZ3XqXRP3G7HXrCJLvadPny62bt0q0tPTxeHDh8XgwYOFh4eHOHHihMO7nzt3Tvj6+ornn39epKamik2bNomQkBDx5ptvOrR3Gffdd58YNGhQnbreiKXuU6dOFb6+vuLLL78Uv//+u9i2bZuIjo4Wjz76qEN7HzhwQKxbt06kp6eLXbt2iW7duomoqChx9erVOvXOy8sztiuA+Oc//ymOHDki/vOf/wghhJg4caIYOnSoMX/ZdOgJEyaIlJQUMX/+fDUduqbMmzdPNGrUSLi5uYl27dqJAwcOGD/r3LmzSEhIMMm/Zs0a0bRpU+Hm5iZuu+02sXnz5jo2LsUS7zNnzgig3Ktz5851Ly4sc2/cuHGF7lOnTnVo7ylTpoiYmBjh4eEh6tWrJ+Li4sTq1avr3LkMS8/z67FX4CKEZd4vvfSSMW+DBg1EfHx8nT/b4nosPeb79u0T7du3F+7u7qJJkybirbfeEjqdro6tLff+7bffBCC2bdtWx6blscRdq9WKadOmiejoaOHh4SEiIiLEs88+W+cBgKXeO3fuFC1atBDu7u4iKChIDB06VPzxxx917rxjx44Kr81lrgkJCeXamB07dohWrVoJNzc30aRJkxo970cjRB31hykUCoVCoVDUkpt6jItCoVAoFAq5UIGLQqFQKBQKaVCBi0KhUCgUCmlQgYtCoVAoFAppUIGLQqFQKBQKaVCBi0KhUCgUCmlQgYtCoVAoFAppUIGLQqFQKBQKaVCBi0KhcDiGDx/OQw89ZHzfpUsXXnrppTr32LlzJxqNhuzs7Drft0KhqBgVuCgUCrMYPnw4Go0GjUaDm5sbMTExzJgxA51OZ/N9JyYmMnPmTLPy1nWwERkZaTwuXl5etGzZkkWLFtXJvhWKmxEVuCgUCrPp3bs3GRkZnD59mnHjxjFt2jTefffdCvOWlJRYbb+BgYH4+vparTxrM2PGDDIyMjh+/DhPPPEEo0eP5rvvvrO3lkLxt0QFLgqFwmzc3d0JDQ2lcePGPPPMM/To0YNvv/0W+N/tnbfeeovw8HCaNWsGwPnz53n00UcJCAggMDCQ/v37c/bsWWOZer2eV155hYCAAIKCgnj11Ve5cQm1G28VFRcX89prrxEREYG7uzsxMTEsXryYs2fP0rVrVwDq1auHRqNh+PDhABgMBmbPnk1UVBSenp7ceeedrF271mQ/SUlJNG3aFE9PT7p27WriWRW+vr6EhobSpEkTXnvtNQIDA0lOTrbgyCoUCnNRgYtCoagxnp6eJj0r27dvJzU1leTkZDZt2oRWq6VXr174+vqye/du9u7di4+PD7179zZu995777Fs2TKWLFnCnj17uHLlCuvXr69yv8OGDePLL7/kX//6FykpKXz66af4+PgQERHBunXrAEhNTSUjI4MPP/wQgNmzZ7NixQoWLFjAiRMnePnll3niiSf497//DZQGWAMGDKBfv34cPXqUUaNGMXHiRIuOh8FgYN26dVy9ehU3NzeLtlUoFGZSy1WtFQrFTUJCQoLo37+/EEIIg8EgkpOThbu7uxg/frzx8wYNGoji4mLjNp9//rlo1qyZMBgMxrTi4mLh6ekptm7dKoQQIiwsTMyZM8f4uVarFbfccotxX0II0blzZzF27FghhBCpqakCEMnJyRV67tixQwDi6tWrxrSioiLh5eUl9u3bZ5J35MiR4rHHHhNCCDFp0iQRGxtr8vlrr71Wrqwbady4sXBzcxPe3t7CxcVFACIwMFCcPn260m0UCkXNcbFv2KRQKGRi06ZN+Pj4oNVqMRgMPP7440ybNs34ecuWLU16Gn755RfS0tLKjU8pKioiPT2dnJwcMjIyaN++vfEzFxcX2rZtW+52URlHjx7F2dmZzp07m+2dlpZGQUEBPXv2NEkvKSmhdevWAKSkpJh4AMTFxZlV/oQJExg+fDgZGRlMmDCBZ599lpiYGLP9FAqF+ajARaFQmE3Xrl355JNPcHNzIzw8HBcX00uIt7e3yfv8/HzatGnDypUry5UVHBxcIwdPT0+Lt8nPzwdg8+bNNGzY0OQzd3f3GnlcT/369YmJiSEmJoavv/6ali1b0rZtW2JjY2tdtkKhMEWNcVEoFGbj7e1NTEwMjRo1Khe0VMRdd93F6dOnCQkJMTbsZS9/f3/8/f0JCwvj4MGDxm10Oh2HDx+utMyWLVtiMBiMY1NupKzHR6/XG9NiY2Nxd3fn3Llz5TwiIiIAaNGiBYcOHTIp68CBA9XW8UYiIiIYNGgQkyZNsnhbhUJRPSpwUSgUNmPIkCHUr1+f/v37s3v3bs6cOcPOnTt58cUXuXDhAgBjx47l7bffZsOGDfz22288++yzVT6DJTIykoSEBEaMGMGGDRuMZa5ZswaAxo0bo9Fo2LRpExcvXiQ/Px9fX1/Gjx/Pyy+/zPLly0lPT+fnn39m3rx5LF++HICnn36a06dPM2HCBFJTU1m1ahXLli2rUb3Hjh3Lxo0b+emnn2q0vUKhqBwVuCgUCpvh5eXFrl27aNSoEQMGDKBFixaMHDmSoqIi/Pz8ABg3bhxDhw4lISGBuLg4fH19efjhh6ss95NPPmHgwIE8++yzNG/enNGjR3Pt2jUAGjZsyPTp05k4cSINGjTg+eefB2DmzJm88cYbzJ49mxYtWtC7d282b95MVFQUAI0aNWLdunVs2LCBO++8kwULFjBr1qwa1Ts2Npb777+f//u//6vR9gqFonI0orIRcAqFQqFQKBQOhupxUSgUCoVCIQ0qcFEoFAqFQiENKnBRKBQKhUIhDSpwUSgUCoVCIQ0qcFEoFAqFQiENKnBRKBQKhUIhDSpwUSgUCoVCIQ0qcFEoFAqFQiENKnBRKBQKhUIhDSpwUSgUCoVCIQ0qcFEoFAqFQiEN/w9Zld5YO0SA0AAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def sm2(history):\n",
    "    ivl = 0\n",
    "    ef = 2.5\n",
    "    reps = 0\n",
    "    for delta_t, rating in history:\n",
    "        delta_t = delta_t.item()\n",
    "        rating = rating.item() + 1\n",
    "        if rating > 2:\n",
    "            if reps == 0:\n",
    "                ivl = 1\n",
    "                reps = 1\n",
    "            elif reps == 1:\n",
    "                ivl = 6\n",
    "                reps = 2\n",
    "            else:\n",
    "                ivl = ivl * ef\n",
    "                reps += 1\n",
    "        else:\n",
    "            ivl = 1\n",
    "            reps = 0\n",
    "        ef = max(1.3, ef + (0.1 - (5 - rating) * (0.08 + (5 - rating) * 0.02)))\n",
    "        ivl = max(1, round(ivl+0.01))\n",
    "    return ivl\n",
    "\n",
    "dataset['sm2_interval'] = dataset['tensor'].map(sm2)\n",
    "dataset['sm2_p'] = np.exp(np.log(0.9) * dataset['delta_t'] / dataset['sm2_interval'])\n",
    "cross_comparison = dataset[['sm2_p', 'p', 'y']].copy()\n",
    "\n",
    "R_Metric = mean_squared_error(cross_comparison['y'], cross_comparison['sm2_p'], squared=False) - mean_squared_error(cross_comparison['y'], cross_comparison['p'], squared=False)\n",
    "print(\"R_Metric: \", R_Metric)\n",
    "plot_brier(dataset['sm2_p'], dataset['y'], bins=40)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(6, 6))\n",
    "\n",
    "cross_comparison['SM2_B-W'] = cross_comparison['sm2_p'] - cross_comparison['y']\n",
    "cross_comparison['SM2_bin'] = cross_comparison['sm2_p'].map(lambda x: round(x, 1))\n",
    "cross_comparison['FSRS_B-W'] = cross_comparison['p'] - cross_comparison['y']\n",
    "cross_comparison['FSRS_bin'] = cross_comparison['p'].map(lambda x: round(x, 1))\n",
    "\n",
    "plt.axhline(y = 0.0, color = 'black', linestyle = '-')\n",
    "\n",
    "cross_comparison_group = cross_comparison.groupby(by='SM2_bin').agg({'y': ['mean'], 'FSRS_B-W': ['mean'], 'p': ['mean', 'count']})\n",
    "print(f\"Universal Metric of FSRS: {mean_squared_error(cross_comparison_group['y', 'mean'], cross_comparison_group['p', 'mean'], sample_weight=cross_comparison_group['p', 'count'], squared=False):.4f}\")\n",
    "cross_comparison_group['p', 'percent'] = cross_comparison_group['p', 'count'] / cross_comparison_group['p', 'count'].sum()\n",
    "plt.scatter(cross_comparison_group.index, cross_comparison_group['FSRS_B-W', 'mean'], s=cross_comparison_group['p', 'percent'] * 1024, alpha=0.5)\n",
    "plt.plot(cross_comparison_group['FSRS_B-W', 'mean'], label='FSRS by SM2')\n",
    "\n",
    "cross_comparison_group = cross_comparison.groupby(by='FSRS_bin').agg({'y': ['mean'], 'SM2_B-W': ['mean'], 'sm2_p': ['mean', 'count']})\n",
    "print(f\"Universal Metric of SM2: {mean_squared_error(cross_comparison_group['y', 'mean'], cross_comparison_group['sm2_p', 'mean'], sample_weight=cross_comparison_group['sm2_p', 'count'], squared=False):.4f}\")\n",
    "cross_comparison_group['sm2_p', 'percent'] = cross_comparison_group['sm2_p', 'count'] / cross_comparison_group['sm2_p', 'count'].sum()\n",
    "plt.scatter(cross_comparison_group.index, cross_comparison_group['SM2_B-W', 'mean'], s=cross_comparison_group['sm2_p', 'percent'] * 1024, alpha=0.5)\n",
    "plt.plot(cross_comparison_group['SM2_B-W', 'mean'], label='SM2 by FSRS')\n",
    "\n",
    "plt.legend(loc='lower center')\n",
    "plt.grid(linestyle='--')\n",
    "plt.title(\"SM2 vs. FSRS\")\n",
    "plt.xlabel('Predicted R')\n",
    "plt.ylabel('B-W Metric')\n",
    "plt.xlim(0, 1)\n",
    "plt.xticks(np.arange(0, 1.1, 0.1))\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "fsrs4anki",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
